Webinar: When are evolutionary algorithms provably efficient? Runtime analysis of population-based evolutionary algorithms

Date: September 18, 2015 3:00pm (UK time)
Registration: https://attendee.gotowebinar.com/register/555560504610023682
Speaker: Dr. Per Kristian Lehre, School of Computer Science, University of Nottingham,  UK

 

 

Abstract:

Populations are at the heart of evolutionary algorithms (EAs). They provide the genetic variation which selection acts upon. A complete picture of EAs and their efficiency can only be obtained if we understand their population dynamics. A rich theory on runtime analysis (also called time-complexity analysis) of EAs has been developed over the last 20 years. The goal of this theory is to show, via rigorous mathematical means, how the efficiency of EAs depends on their parameter settings and the characteristics of the underlying fitness landscapes. Initially, runtime analysis of EAs was mostly restricted to simplified EAs that do not employ large populations, such as the (1+1) EA.

This webinar introduces recent, and easy to use techniques that make runtime analysis of complex, population-based evolutionary algorithms possible. It first offers an overview of population-based evolutionary algorithms. In particular, it defines common stochastic selection mechanisms and explains how to measure their selective pressure.  The main part of the webinar covers in detail widely applicable techniques tailored to the analysis of populations, in particular drift analysis and level-based analysis.

To illustrate the application of these techniques, we consider several fundamental questions: When are populations necessary for efficient optimisation with EAs? What is the appropriate balance between exploration and exploitation and how does this depend on relationships between mutation and selection rates? What determines an EA's tolerance for uncertainty, e.g. in form of noisy or partially available fitness?

The webinar is aimed at students and researchers who wish to gain a deeper theoretical understanding of evolutionary algorithms, and possibly initiate their own research in runtime analysis. No more than a basic knowledge of probability theory will be required. 

Biography:

Per Kristian Lehre received MSc and PhD degrees in Computer Science from the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway. He finished the PhD in 2006 under the supervision of Prof Pauline Haddow, and joined the School of Computer Science at The University of Birmingham, UK, as a Research Fellow in January 2007 with Prof Xin Yao. He was a Post Doctoral Fellow at DTU Informatics, Technical University of Denmark in Lyngby, Denmark from April 2010. He is since September 2011 a Lecturer in the School of Computer Science at the University of Nottingham, UK.

Dr Lehre's research interests are in theoretical aspects of nature-inspired search heuristics, in particular runtime analysis of population-based evolutionary algorithms.  His research has won numerous best paper awards, including GECCO (2013, 2010, 2009, 2006) and ICSTW (2008). He is vice-chair of IEEE Task Force on Theoretical Foundations of Bio-inspired Computation, and a member of the editorial board of Evolutionary Computation. He has guest-edited special issues of Theoretical Computer Science and IEEE Transaction on Evolutionary Computation on theoretical foundations of evolutionary computation. Dr Lehre has given many tutorials on evolutionary computation in summer schools (UK: 2007, France: 2009, 2010, and 2011, Estonia: 2010), as well as major conferences and workshops (GECCO 2013, 2014, 2015, CEC 2013, and 2015, ThRaSH 2013).  He is the main coordinator of the 2M euro EU-funded project SAGE which brings together theory of evolutionary
computation and population genetics.

Call for Papers: WCCI 2016 Special Session "Advances to Type-2 Fuzzy Logic Control"

Aim and Scope

Type-2 fuzzy logic control is a technology which takes the fundamental concepts in control from type-1 fuzzy logic and expands upon them in order to deal with higher levels of uncertainty presented in many real-world control problems. A variety of control application areas have been addressed with type-2 fuzzy logic, from the control in steel production plants to the control of marine diesel engines and robotic control. For some engineering applications, there is evidence that type-2 fuzzy logic can provide benefits over both traditional forms of control as well as type-1 fuzzy logic. It is the aim of this special session to attract a comprehensive selection of high quality current research in this area of type-2 control, motivating further collaboration and providing a platform for the discussion on future directions of type-2 fuzzy logic control by active researchers in the field. This special session will address advances in interval type-2 as well as general type-2 fuzzy logic control. Topics include, but are not limited to:

• Interval Type-2 Fuzzy Logic Control
• General Type-2 Fuzzy Logic Control
• Type-2 TSK Fuzzy Logic Control
• PID type Type-2 Fuzzy Logic Control
• Model-Based Type-2 Fuzzy Logic Control
• Adaptive / Self-Tuning Type-2 Fuzzy Control 
• Neuro-Fuzzy Type-2 Control
• Applications of Type-2 Fuzzy Controllers

Information for Authors

1. Information on the format and templates for papers can be found here: http://www.wcci2016.org/submission.php
2. Papers should be submitted via the FUZZ 2016 paper submission site: http://ieee-cis.org/conferences/fuzzieee2016/upload.php 
3. Select the Special Session name “Advances to Type-2 Fuzzy Logic Control” in the Main Research topic dropdown list
4.  Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of January 15, 2016

Names of Organizers

Asst. Prof. Dr. Tufan KUMBASAR
Istanbul Technical University, Turkey,
kumbasart@itu.edu.tr

Prof. Hao YING,
Wayne State University,
Detroit, USA, hao.ying@wayne.edu

TUFAN KUMBASAR is an Assistant Professor in the Department of Control and Automation at the Istanbul Technical University, Faculty of Electrical and Electronics Engineering, Turkey. He is also the co-director of the ABB Process Control Laboratory at the Istanbul Technical University. Dr. Tufan Kumbasar has participated in leading positions in many national and international projects as principal, main investigator, researcher and consultant. He also works as a peer reviewer for about 25 international journals such as IEEE Transactions on Fuzzy Systems, Soft Computing, Journal of Intelligent and Fuzzy Systems and Applied Soft Computing. He is also a member of the IEEE Computational Intelligence Society (CIS). He has served recently as a Panel Session Co-Chair in FUZZ 2015 where he also has co-organized the special session entitled “Advances to Type-2 Fuzzy Logic Control”. His major research interests are in computational intelligence, notably type-2 fuzzy systems, fuzzy logic, neural networks, evolutionary algorithms and control theory. He is also interested in process control, robotics and intelligent control and their real-world applications. He has currently authored more than 50 papers in international journals, conferences and books. Dr. Kumbasar received the Best Paper Award from the IEEE International Conference on Fuzzy Systems in 2015.

HAO YING is Professor in the Department of Electrical and Computer Engineering, Wayne State University, Detroit, USA. He is an IEEE Fellow. He has published one single-author research monograph/advanced textbook entitled Fuzzy Control and Modeling: Analytical Foundations and Applications (IEEE Press, 2000, 342 pages; foreword by Professor Lotif A. Zadeh), which contains solely his own research results. He has coauthored another book titled Type-2 Fuzzy Logic Control: Introduction to Theory and Applications (John Wiley & Sons, Inc., 2014). He holds one U.S. patent and has published almost 100 peer-reviewed journal papers and over 140 peer-reviewed conference papers. Prof. Ying's work has been widely cited - his h-index is 35 (the 35 publications included in his index have by themselves generated more than 3,200 citations so far). He is serving as an Associate Editor or a Member of Editorial Board for 9 international journals. He is a member of the Fuzzy Systems Technical Committee of the IEEE Computational Intelligence Society. He was elected to serve as a board member of the North American Fuzzy Information Processing Society (NAFIPS) for two terms (2005-2008 and 2008-2011). He served as Program Chair for the 2005 NAFIPS Conference and Program Co-Chair for the 2010 NAFIPS Conference as well as for the International Joint Conference of NAFIPS Conference, Industrial Fuzzy Control and Intelligent System Conference, and NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic held in 1994. He served as the Publication Chair for the 2000 IEEE International Conference on Fuzzy Systems and the Competition Chair for this annual conference in 2009 and 2011. He also served as a Program Committee Member for over 50 international conferences. He was invited to serve as reviewer for nearly 80 international journals, which are in addition to major international conferences and book publishers.

Call for Papers: WCCI 2016 Special Session Computational Intelligence Methodologies for Environmental Sustainability and Sustainable Development: Theory and Applications

Scope and Motivation:

Environmental sustainability has become a topic of particular interest - and concern in - in the last 20 years. Environmental sustainability is focused upon responsible decision-making and action-taking for the protection of the environment, thus boosting the ability of the environment to continue to support life. At the same time, environmental sustainability tackles the issue of developing optimal practices that will reduce - and eventually minimise - the negative impact on the environment. Further to pollution, waste, and energy reduction, environmental sustainability aims at developing processes that will help human societies to become completely sustainable in the future. The use of non-parametric, noise-resistant, and learn-by-example approaches is pertinent to this end, and constitutes the focus of this WCCI’16 Special Session, a sequel to the IJCNN'15 Special Session under the same name.

Topics:

• Environmental sustainability
• Sustainable development
• Decision making
• Action taking
• Optimisation
• Long-, medium- and long-term impact assessment
• Human activity and the environment
• Product life-cycle

Relevance to WCCI'16

Artificial neural networks, genetic algorithms, and fuzzy expert systems have demonstrated their superiority over other traditional approaches when applied to inexact, ill- or partially-defined, time-varying problems. In that sense, WCCI’16 and - in particular - the “Special Session on Computational Intelligence Applications to Environmental Sustainability and Sustainable Development: Theory and Applications” shall prove to be a focus of attention of leaders in/researchers of environmental sustainability and sustainable development.

Short Resumes of Organisers:

Tatiana Tambouratzis: Associate professor at the Department of Industrial Management & Technology, University of Piraeus, Greece; held positions at the Institutes of Informatics and Nuclear Technology & Radiation Protection, NCSR "Demokritos", and at the Department of Nuclear Engineering, Chalmers University of Technology, Goteborg, Sweden; a Greek State Scholarship Foundation National Research Institute (Greece), Royal Society and SERC (U.K.), and Fulbright (U.S.A.) scholar; Fellow of the Institute of Mathematics and its Applications (FIMA); evaluator of national and EU-funded projects; advisory and/or editorial board member, reviewer of peer-reviewed international scientific journals and conferences; organiser of international scientific conferences and special sessions; supervisor, internal examiner and member of the Examination Board of PhD theses, as well as M.Sc. and B.Sc. dissertations (Greece, Italy, Sweden); author or co-author of 43 publications in peer-reviewed international scientific journals, 54 international scientific conference proceedings, five books and five technical reports; invited speaker at various universities in Greece, Europe and the United States, as well as at international scientific conferences; main research interests in artificial and computational intelligence, brain function, natural and artificial vision, psychophysics and cognitive psychology, optimisation, monitoring and prediction, wavelets, signal processing, signals and systems, energy systems, safety, environmental sustainability.

Andreas-Georgios Stafylopatis: Professor at the School of Electrical and Computer Engineering, National Technical University of Athens, Greece; director of the Intelligent Systems Laboratory; Head of the School (2010-2013); main research interests in the modelling and performance evaluation of computer, intelligent systems and computational intelligence, with application to pattern recognition, classification and diagnosis, data mining and knowledge extraction; supervisor of 24 PhD students; leader or key researcher in more than 50 national and EU-funded research projects; author or coauthor of approximately 180 refereed papers, of which more than 60 in international journals, with about 1000 citations; chairman of a many international scientific conferences; invited speaker/author in many conferences/books and journals; associate editor of scientific journals and reviewer for a large number of scientific journals and conferences; evaluator of research proposals for national and international organisations; book evaluator for Greek and international publishers; has served as scientific consultant and member of advisory/evaluation committees concerning large computer system projects in various ministries and public sector organizations; has acted as a Director of the Computer Science Section of the School, as a Coordinator of the Graduate Studies Program of the School; is a member of the Technical Chamber of Greece, IEEE Computer Society, IEEE Computational Intelligence Society, IEEE Systems, Man, and Cybernetics Society, and the Association for Computing Machinery (ACM).

Assoc. Professor Kostas Karatzas, Dr.-Eng., holds a Diploma and a Doctor degree in Mechanical Engineering, and leads the Informatics Systems and Applications – Environmental Informatics Research Group at the Dept. of Mechanical Engineering, where he teaches Informatics, Environmental Informatics and Environmental Impact Assessment. He is also teaching/has taught in various EU universities in MSc and PhD seminar level, while he has been a visiting professor for the Finnish Meteorological Institute (FMI) and an Adjunct Professor for the University of Western Macedonia, Greece. The research work of Dr. Karatzas focuses mainly in informatics applications and environmental informatics with personalised service orientation, urban environment management and information systems, environmental data analysis and forecasting with the aid of computational intelligence methods and mathematical models, multimedia information content tools, and participatory environmental sensing. Dr. Karatzas has participated in more than 30 European R&D projects, is Member of the International Scientific Advisory Board (SAB) of CLEEN’s Measurement, Monitoring and Environmental Efficiency Assessment (MMEA) research programme, and an Associate Member of the OGC. He has authored approx 200 scientific papers, has been a member of the scientific committee of the many Environmental Informatics and Computational Intelligence conferences, and has/is supervising a number of PhD and MSc thesis in the area of Environmental Informatics-environmental information analysis and modelling.

Professor Mikko Kolehmainen, originally a system analyst and chief software engineer in the software industry developing solutions for energy companies, moved to the academia in the 90’s working as a researcher in bioinformatics and environmental sciences. This was followed by a nomination to research director and - subsequently - professor of environmental informatics. Currently professor and leader of the research group of environmental informatics, University of Eastern Finland (UEF), lecturing and developing courses on environmental data mining, environmental bioinformatics and ecological risk assessment. In the future, my goal is to create strong international research in the focus areas, as well as develop e-learning to enable students worldwide to take part in the studies of environmental of environmental informatics and modeling. Current focus of research: environmental safety and security, sustainable energy systems. Professional goals: developing methods for utilizing data and databases in the information society; modeling of complex systems in life sciences.

Call for Papers WCCI 2016 Special Session Evolutionary Computation for Music, Art, and Creativity

http://cilab.cs.ccu.edu.tw/ci-tf/ECMAC2016.html

Aim and Scope

Evolutionary computation (EC) techniques, including genetic algorithm, evolution strategies, genetic programming, particle swarm optimization, ant colony optimization, differential evolution, and memetic algorithms, have shown to be effective for search and optimization problems. Recently, EC gained several promising results and becomes an important tool in computational creativity, such as in music, visual art, literature, architecture, and industrial design.
The aim of this special session is to reflect the most recent advances of EC for Music, Art, and Creativity, with the goal to enhance autonomous creative systems as well as human creativity. This session will allow researchers to share experiences and present their new ways for taking advantage of EC techniques in computational creativity. Topics of interest include, but are not limited to, EC technologies in the following aspects:

• Generation of music, visual art, literature, architecture, and industrial design
• Algorithmic design in creative intelligence
• Optimization in creativity
• Development of hardware and software for creative systems
• Evaluation methodologies
• Assistance of human creativity
• Computational aesthetics
• Emotion response
• Human-machine creativity

Keywords

Evolutionary computation, computational creativity, music, visual art, creative intelligence, emotion response, and aesthetics

Organizers:

This special session is organized by IEEE CIS ETTC Task Force on Creative Intelligence.

Chuan-Kang Ting   
National Chung Cheng University, Taiwan   
Chuan-Kang Ting (S’01–M’06¬–SM’13) received the B.S. degree from National Chiao Tung University, Taiwan, in 1994, the M.S. degree from National Tsing Hua University, Taiwan, in 1996, and the Ph.D. degree from the University of Paderborn, Germany, in 2005. He is currently an Associate Professor with the Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan. His research interests are in evolutionary computation, computational intelligence, metaheuristic algorithms, and their applications in music, art, computer networks, bioinformatics and games.

Francisco Fernández de Vega   
University of Extremadura, Spain    
Francisco Fernández is Associate Professor at the University of Extremadura. He received his BS from the University of Seville 1993, MS from the University of Seville 1997, and Ph. D from the University of Extremadura 2001. His research interests include Parallel and Distributed Evolutionary Algorithms and their applications to multiple aspects of art and design. He's been guest editor with Soft Computing, Parallel Computing, Journal of Parallel and Distributed, Natural Computing and edited the books Parallel and Distributed Computational Intelligence and Parallel Architectures and Bioinspired Algorithms, with Springer. He is cochair of EvoPar, part of Evo* Conference. He has published more than 200 papers in conferences and journals.  His work was recently awarded with the 2013 ACM GECCO Art, Design and Creativity Competition.

Palle Dahlstedt   
University of Gothenburg, Sweden   
Palle Dahlstedt is active both as a researcher in the field of computational creativity, and as an internationally recognized composer and improviser. He is associate professor in computer-aided creativity at the Dept. of Applied Information Technology, University of Gothenburg & Chalmers University of Technology, Sweden, and main lecturer in electronic and computer music and artistic director of the Lindblad Studios at the Academy of Music and Drama, University of Gothenburg. His music has been performed on six continents, and received prizes such as the prestigeous Gaudeamus Prize 2001. He has published extensively within the field, and is currently directing a major research project around technology-based creativity in musical performance.

WCCI 2016 Keynote Speaker

The 2016 IEEE CIS Evolutionary Computation Pioneer Award winner and 2015 IEEE Frank Rosenblatt Award winner, Professor Marco Dorigo (IEEE Fellow), will receive his award and deliver a keynote at IEEE WCCI 2016.
http://wcci2016.org/speakers.php.

WCCI 2016 Best Paper Awards

IEEE WCCI 2016 will present the Best Overall Paper Awards and the Best Student Paper Awards to recognize outstanding papers published in each of the three conference proceedings (IJCNN 2016, FUZZ-IEEE 2016, IEEE CEC 2016). The awards will be judged by an Awards Committee and the recipient of each award will be given a certificate of the award and a cash prize to be presented during the conference banquet at IEEE WCCI 2016.
http://wcci2016.org/news.php?id=august

Call for Papers WCCI 2016 Special Session: Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE)

WEBSITE: http://www.tech.dmu.ac.uk/~mmavrovouniotis/ECiDUE16/

AIMS AND SCOPE

Many real-world optimization problems are subject to dynamism and uncertainties that are often  impossible to avoid in practice. For instance, the fitness function is uncertain or noisy as a result of simulation/ measurement errors or approximation errors (in the case where surrogates  are used in place of the computationally expensive high fidelity fitness function). In addition, the design variables or environmental conditions can be perturbed or they change over time.

The tools to solve these dynamic and uncertain optimization problems (DOP) should be flexible, able to tolerate uncertainties, fast to allow reaction to changes and adaptive. Moreover, the objective of such tools is no longer to simply locate the global optimum solution, but to continuously track the optimum in dynamic environments, or to find a robust solution that operates properly in the presence of uncertainties.

The last decade has witnessed increasing research efforts on handling dynamic and uncertain optimization problems using evolutionary algorithms and other metaheuristics, and a variety of methods have been reported across a broad range of application backgrounds.

This special session aims at bringing together researchers from both academia and industry to review the latest advances and explore future directions in this field.

Topics of interest include but are not limited to:

• Benchmark problems and performance measures
• Dynamic single - and multi-objective optimization
• Adaptation, learning, and anticipation
• Models of uncertainty and their management
• Handling noisy fitness functions
• Using fitness approximations
• Searching for robust optimal solutions
• Algorithm comparison and benchmarking
• Hybrid approaches
• Theoretical analysis
• Real-world applications

IMPORTANT DATES:

Paper submission:        January 15, 2016
Notification:            March 15, 2016
Final paper submission:  April 15, 2016

INFORMATION FOR AUTHORS:

1. Information on the format and templates for papers can be found here: http://www.wcci2016.org/submission.php 
2. Papers should be submitted via the CEC 2015 paper submission site: http://ieee-cis.org/conferences/cec2016/upload.php 
3. Select "1.bb. Evolutionary Computation in Dynamic and Uncertain Environments" in the main research topic dropdown list.
4. Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of January 15, 2016.

ORGANIZERS:

Dr Michalis Mavrovouniotis: De Montfort University, United Kingdom
email: mmavrovouniotis@dmu.ac.uk

Dr Changhe Li: China University of Geosciences, Wuhan, China.
email: changhe.lw@gmail.com

Prof Shengxiang Yang: De Montfort University, United Kingdom
email: syang@dmu.ac.uk

Prof Yinan Guo: China University of Mining and Technology, China
email: guoyinan@cumt.edu.cn

Call for Papers WCCI 2016 Special Session: Computational Intelligence for Physiological and Affective Computing (CIPAC)

Affective Computing (AC) is "computing that relates to, arises from, or deliberately influences emotions" as initially coined by Professor R. Picard (Media Lab, MIT). It has been gaining popularity rapidly in the last decade because it has great potential in the next generation of human-computer interfaces. One goal of affective computing is to design a computer system that responds in a rational and strategic fashion to real-time changes in user affect (e.g., happiness, sadness, etc.), cognition (e.g., frustration, boredom, etc.) and motivation, as represented by speech, facial expressions, gestures, physiological signals, neurocognitive performance, etc. Physiological Computing (PC) relates to computation that incorporates physiological signals in order to produce useful outputs (e.g., in computer-human interaction). It mainly differs from AC in the sense that its foremost focus is not the modeling of affect but rather the utilization of physiological information generally.

Practical applications of AC and PC based systems seek to achieve a positive impact on our everyday lives by monitoring, recognising and acting on our emotional states and physiological signals. Integrating these sensing modalities into intelligent and pervasive computing systems will reveal a far richer picture of how our fleeting emotional responses, changing moods, feelings and sensations, such as pain, touch, tastes and smells, are a reaction to or influence how we implicitly or explicitly interact with the environment and increasingly the connected computing artifacts within.

The integration and use of AC and PC raise many new challenges for signal processing, machine learning and computational intelligence. Fuzzy Logic Systems in particular provide a highly promising avenue for addressing some of the fundamental research challenges in AC/PC where most data sources such as: body signals (e.g., heart rate, brain waves, skin conductance and respiration) facial features, speech and human kinematics are very noisy/uncertain and subject-dependent. Clearly however, other key areas of Computational Intelligence (CI) research, such as evolutionary learning algorithms and neural network based classifiers provide essential tools to address the significant challenge of AC/PC.

The Computational Intelligence for Physiological and Affective Computing special session aims to bring together researchers from the three areas of CI to discuss how CI techniques can be used individually or in combination to help solve challenging AC/PC problems, and conversely, how physiological and affect (emotion) and its modeling can inspire new approaches in CI and its applications. Topics of interest for this special session include but are not limited to:

• Models of emotion and physiological information
• Classifiers for physiological information
• Applications based on/around physiological information
• Fuzzy set and system based architectures for processing emotions and other affective states
• Automatic emotion recognition & synthesis from physiological signals, facial expressions, body language, speech, or neurocognitive performance
• Multimodal sensor fusion for emotion recognition
• Emotion mining from texts, images, or videos
• Affective interaction with virtual agents and robots based on fuzzy systems
• Physiological and emotion driven control
• Applications of affective computing in interactive learning, affective gaming, personalized robotics, virtual reality, social networking, smart environments, healthcare and behavioral informatics, etc.

As a cross-disciplinary and CI applications oriented special session, accepted and presented papers will be published under one of the three conference proceedings (Fuzzy-IEEE, IJCNN or IEEE CEC) that are most appropriate for the presented research. For paper submissions please visit WCCI IEEE 2016 submissions: http://www.wcci2016.org/submission.php

Important Dates

Paper submission deadline: 15th January 2016
Author notification: 15th March 2016
Deadline for final manuscript: 15th April 2016
Early registration deadline: 15th April 2016
Conference dates: 25th July – 29th July 2016

Program Committee

Egon L. van den Broek, University of Twente, The Netherlands
Hani Hagras, University of Essex, UK
Marie-Jeanne Lesot, LIP6-UPMC, France
Peter Lewis, Aston University, UK
Chin-Teng Lin, National Chiao Tung University, Taiwan
Jiann-Shing Shieh, Yuan Ze University, Taiwan
Shrikanth Narayanan, University of Southern California, USA
Anton Nijholt, University of Twente, The Netherlands
Ana Paiva, Technical University of Lisbon, Portugal
Rahat Iqbal, Coventry University, UK
Mei Si, Rensselaer Polytechnic Institute, USA
Carlo Strapparava, Fondazione Bruno Kessler, Italy
Shangfei Wang, University of Science and Technology of China, China
Dongrui Wu, GE Global Research, USA
Georgios Yannakakis, IT University of Copenhagen, Denmark
Slawomir Zadrozny, Polish academy of science, Poland
Michel Valstar, University of Nottingham, UK
Christopher Peters, KTH Royal Institute of Technology, Sweden
Palaniappan Ramaswamy, University of Kent, UK
Ahmed Kattan, Um Al-Qura University, Saudi Arabia
Guillaume Chanel, Swiss Center for Affective Science, Switzerland
Victor Zamudio, Instituto Tecnologico de Leon, Mexico
Ginevra Catellano, University of Birmingham, UK
Vasile Palade, Coventry University, UK

Organisers

Dr Faiyaz Doctor
School of Computing, Electronics and Maths
Faculty of Engineering, Environment & Computing
Coventry University
Email: faiyaz.doctor AT coventry.ac.uk
http://www.coventry.ac.uk/research/research-directories/researchers/faiyaz-doctor/
Dr. Faiyaz Doctor is a Senior Lecturer in the Faculty of Engineering and Computing at Coventry University. He has previously worked jointly in industry and academia to develop novel artificial intelligence solutions for addressing real world problems related to smart environments, energy optimization, predictive analytics and decision support. His work has resulted in high profile innovation awards (Best KTP Regional Finalist 2011, Load Stafford Award for Innovation) and an international patent on improved approaches for data analysis and decision-making using hybrid neuro-fuzzy and type-2 fuzzy systems: WO/2009/141631. He has previously been a co-investigator on a Technology Strategy Board funded project on developing driver prediction models using artificial intelligence approaches in collaboration with Jaguar Land Rover Ltd. His research interests are in the area of computational intelligence with an emphasis on fuzzy logic, type-2 fuzzy logic and hybrid systems where his research has been applied to ambient intelligence, pervasive and affective computing, industrial automation and biomedical systems. Dr. Doctor has published over 40 papers in peer reviewed international journals, conferences and workshops. He currently chairs the IEEE Computational Intelligence Society’s Emergent Technologies "Affective Computing" Task Force and has been co-organizer of the special session on Fuzzy Systems for Physiological and Affective Computing (FSPAC) at the 2015 IEEE International Conference on Fuzzy Systems and the special session on Computational Intelligence for Physiological and Affective Computing (CIPAC) and co-chair at the special session on Brain and Physiological Computation for Affective Computing at the 2014 IEEE World Congress on Computational Intelligence. He has been a guest editor for the Journal of Ambient Intelligence and Smart Environments (JAISE), Thematic Issue on Affect Aware Ubiquitous Computing and has served as co-organiser of the International Workshop on Applications of Affective Computing in Intelligent Environments (ACIE 2013, 2014) in conjunction with the International Conference on Intelligent Environments. He is also and member of the IEEE and IEEE Computational Intelligence Society.

Dr Christian Wagner
Horizon Digital Economy Institute & Intelligent Modeling and Analysis Group
School of Computer Science
University of Nottingham, UK
Email: christian.wagner AT nottingham.ac.uk
http://ima.ac.uk/wagner
Christian Wagner is an Associate Professor in Computer Science at the University of Nottingham, UK. He received his PhD in Computer Science from the University of Essex in 2009 after which he was involved both in the management and scientific work of the EU FP7 project ATRACO, joining the University of Nottingham in 2011. His main research interests are centred on uncertainty handling, approximate reasoning (reasoning in the face of uncertainty, lack of knowledge and vagueness), decision support and data-driven decision making using computational intelligence techniques. Recent applications of his research have focused in particular on decision support in environmental and infrastructure planning & management contexts as well as cyber-security. He has published more than 60 peer-reviewed articles in international journals and conferences, two of which recently won best paper awards (Outstanding IEEE Transactions on Fuzzy Systems paper 2013 (for a paper in 2010) and a best paper award for a Fuzz-IEEE 2012 conference paper), and several book chapters. Dr Wagner is currently active PI and Co-I on a number of research projects, with overall funding as PI of £1 million and funding as Co-I of 2 million. He is an Associate Editor of the IEEE Transactions on Fuzzy Systems journal (IF: 6.3) and is actively involved in the academic community through for example the organization of special sessions at premiere IEEE conference such as the World Congress on Computational Intelligence 2014 and the IEEE Conference on System, Man and Cybernetics 2015. He has developed and been involved in the creation of multiple open source software frameworks, making cutting edge research accessible both to peer researchers as well as to different (multidisciplinary - beyond computer science) research and practitioner communities, including R and Java based toolkits for type-2 fuzzy systems in use in more than ten countries.

Dr Dongrui Wu
DataNova, NY, USA
Email: drwu09 AT gmail.com
https://sites.google.com/site/drwu09/
Dongrui Wu received a PhD in Electrical Engineering from the University of Southern California (USC) in 2009. He was a Research Associate in the USC Institute for Creative Technologies and Signal Analysis & Interpretation Laboratory (SAIL) 2009-2010, and a Lead Research Engineer in the Machine Learning Lab of GE Global Research 2010-2015. Now he is starting his own business. Dr. Wu's research interests include affective computing, brain-computer interaction, computational intelligence, intelligent control, machine learning, optimization, and text analysis. He has over 80 publications, including a book "Perceptual Computing." He received IEEE Computational Intelligence Society (CIS) Outstanding PhD Dissertation Award in 2012, IEEE Transactions on Fuzzy Systems Outstanding Paper Award in 2014, and NAFIPS Early Career Award in 2014. He was a selected participant of the 1st Heidelberg Abel/Fields/Turing Laureate Forum in 2013, NAE 2015 German-American Frontiers of Engineering, and the 13th Annual National Academies Keck Futures Initiative (NAKFI) conference in 2015. Dr. Wu had worked on a broad range of projects from GE Capital, Healthcare, Transportation, Power and Water, and Oil & Gas. Two of his projects won the prestigious CIO 100 Awards in 2012 (TrueSense for GE Water) and 2014 (Fleet Optimizer for GE Capital), respectively. Additionally, he received 10 Above and Beyond Awards for outstanding performance. Dr. Wu is an Associate Editor of IEEE Transactions on Fuzzy Systems, IEEE Transactions on Human-Machine Systems, and PeerJ Computer Science. He was the lead Guest Editor of the IEEE Computational Intelligence Magazine Special Issue on Computational Intelligence and Affective Computing, and former Chair of the IEEE CIS Affective Computing Task Force. He is a Senior Member of IEEE, and an Executive Committee member of the Association for the Advancement of Affective Computing (AAAC).

Dr Marie-Jeanne Lesot (TBC)
Université Pierre et Marie Curie
Laboratoire d'Informatique de Paris 6, LIP6
Email: Marie-Jeanne.Lesot AT lip6.fr
http://webia.lip6.fr/~lesot/
Marie-Jeanne Lesot obtained her PhD in 2005 from the University Pierre et Marie Curie in Paris. Since 2006 she has been an associate professor in the department of Computer Science Lab of Paris 6 (LIP6) and a member of the Learning and Fuzzy Intelligent systems (LFI) group. Her research interests focus on fuzzy machine learning with an objective of data interpretation and semantics integration and, in particular, to model and manage subjective information; they include similarity measures, fuzzy clustering, linguistic summaries, affective computing and information scoring. She has published 43 international journal and conference papers and co-edited a book on scalable fuzzy algorithms for data management and analysis. She has also participated in various joint projects with companies, on topics such as fraud detection, dynamic monitoring of information propagation, emotional design and emotion mining among others.

Call for Papers WCCI 2016 Special Session: Computational Intelligence for Industry 4.0

Aim:

This Special Session is dedicated to the latest developments of computational intelligence (CI) for Industry 4.0, the first a-priori engineered (and the fourth) 'Industrial Revolution'.  Focusing on smart manufacturing and cyber-physical systems so far, efforts in Industry 4.0 have lacked smart design and business elements for manufacture that are necessary in completing this unprecedented upgrade of value chain.  Computational intelligence has however provided an extra-numeric, as well as efficiently-numeric, tool to realise this goal.  The Special Session therefore encourages and reports applications to Industry 4.0 in the era of interactive cloud computing and data science.

Scope:

Computational intelligence, primarily comprising artificial neural network and learning systems, evolutionary computation, and fuzzy logic and systems, is a set of nature-inspired modelling and optimisation approaches to complex real-world problems, to which traditional approaches such as first principles modelling and statistical or curve fitting are ineffective or incapable of addressing.  We are soliciting original research papers or reviews that would shape and advance a smart design and business environment for Industry 4.0.  Papers addressing how to revolutionise the way that smart designs are created and smart machines are built, thereby leading to a step improvement in manufacturing autonomy and industrial efficiency, performance and competitiveness, will be most welcome.

Main Topics (include but are not limited to):

• Computer intelligence or machine learning for cyber-physical systems;
• Computer-automated design, machine learning or intelligent search for Industry 4.0;
• Computational intelligence for smart design for smart manufacture;
• Computational intelligence for Industry 4.0 in cloud and big data environments;
• Computational intelligence and data science applications to marketing for design;
• Computational intelligence and data science for marketing and service in Industry 4.0 value chain;
• Computational intelligence or other learning techniques for Industry 4.0 business informatics and risk management;
• Computational intelligence for Industry 4.0 digital economy;
• Evolutionary distributed or cloud computing for interactive product design and marketing;
• Evolutionary big data interaction for predictive product design and marketing.

Submission by January 2016 at Congress website http://www.wcci2016.org/.

Conference Proceedings:

This is a cross-disciplinary and CI applications Special Session.  Therefore, a submitted paper (if duly accepted and presented) will be published under one of the three conference proceedings (IEEE CEC, Fuzzy-IEEE, or IJCNN) that is most appropriate to the paper.  Such decision will be made by the Special Session Organizers in consultation with the Special Session Chair and one of the three Conference Chairs.

Names of Organisers:

Professor Yun Li
School of Engineering
University of Glasgow, U.K.
Yun.Li@glasgow.ac.uk

Dr. Leo Chen
School of Engineering and Built Environment
Glasgow Caledonian University, U.K.
Leo.Chen@gcu.ac.uk

Asso. Prof. Cindy Goh
University of Glasgow Singapore
Republic of Singapore
Cindy.Goh@glasgow.ac.uk

Asso. Prof. Zhi-Hui Zhan
School of Advanced Computing
Sun Yat-sen University, China
zhanzhh@mail.sysu.edu.cn

Short Biography of the Organizers:

Yun Li received his PhD from University of Strathclyde, U.K., in 1990. During 1989 and 1990, he was with U.K. National Engineering Laboratory and Industrial Systems and Control Ltd. He joined University of Glasgow as Lecturer in 1991, was Founding Director of University of Glasgow Singapore during 2011-2013 and served as Founding Director of the University's international joint programme with University of Electronic Science and Technology of China in 2013. He established and chaired both the IEEE Computer-Aided Control System Design Evolutionary Computation Working Group and the European Network of Excellence in Evolutionary Computing Workgroup on Systems, Control, and Drives for Industry in 1998. Professor Li is a Chartered Engineer in the U.K. and is currently an Associated Editor of IEEE Transactions on Evolutionary Computation.  He has over 200 publications and one of them has been noted the most popular article every month in IEEE Transactions on Control Systems Technology.

Leo Chen, PhD, CEng, is currently Lecturer in Dynamics and Control at Glasgow Caledonian University. His research which has been published in scholarly journals and edited volumes, explores the aspects: computational intelligence, dynamics and control, multidisciplinary design and optimisation under uncertainty; reliability and risk analysis; dynamics and intelligent control, with the modelling and simulation of robotics, automotive systems, space tether systems, MOS device reliability, computational finance and optical engineering, etc. Dr. Chen also studies how people construct evaluations and preferences in social contexts.  He has recently served as Guest Editor of Mathematical Problems in Engineering Special Issue on Computational Intelligence Approaches to Robotics, Automation, and Control.

Cindy Goh received her PhD from the University of Glasgow, U.K., in 2004. From 2011 to 2013, she was an Assistant Professor at the University of Glasgow, Singapore (UGS). In 2013, she was promoted to Associate Professor and became the Director of Research Programmes at UGS where she has overall responsibility for its research strategy and knowledge exchange portfolio. Her research interest is in intelligent optimisation and data analytics for optimal decision making and design to advance the state-of-the-art in complex engineering systems, energy and transport networks, and smart manufacturing. Her work has been published in internationally peer reviewed journals. She is a member of the IEEE, and a founding member of the International Union of Radio Science Committee, Singapore.

Zhi-Hui Zhan received his Bachelor's and PhD degrees from the Department of Computer Science of Sun Yat-Sen University, Guangzhou, China, in 2007 and 2013, respectively.  He is currently an Associate Professor with the School of Advanced Computing, Sun Yat-sen University. His research interests include evolutionary computation, swarm intelligence, and their applications to real-world problems and in environments of cloud computing and big data.  His PhD dissertation received the China Computer Federation Outstanding Dissertation Award in 2013.  Dr. Zhan also received an award of the Natural Science Foundation for Distinguished Young Scientists of Guangdong Province, China, in 2014 and the Pearl River New Star in Science and Technology Award in 2015. Dr. Zhan is listed by Thomson Reuters as one of the Most Cited Chinese Researchers in Computer Science.

WCCI 2016 Travel Grants

The IEEE Computational Intelligence Society (IEEE CIS) will offer a limited number of Travel Grants for Students (undergraduate or graduate students, from any country) and Professional Researchers from Developing Countries ( https://goo.gl/d3JGxM ) who are presenting one or more papers at IEEE WCCI 2016. Check http://wcci2016.org/sponsors.php?id=grants for more information.

IEEE Transactions on Fuzzy Systems, vol. 23, issue 4, 2015

1. Fuzzy Adaptive Output Feedback Control of MIMO Nonlinear Systems With Partial Tracking Errors Constrained
Author(s):  Shaocheng Tong, Shuai Sui, and Yongming Li
Page(s):  729-742

2. Time-Validating-Based Atanassov's Intuitionistic Fuzzy Decision Making
Author(s):  Liang-Hsuan Chen and Chien-Cheng Tu
Page(s):  743 - 756

3. Gain Tuning of Fuzzy PID Controllers for MIMO Systems: A Performance-Driven Approach
Author(s):  Paulo Gil, Catarina Lucena, Alberto Cardoso, and Luis Brito Palma
Page(s):  757 - 768

4. A Novel Approach to Building a Robust Fuzzy Rough Classifier
Author(s):  Suyun Zhao, Hong Chen, Cuiping Li, Xiaoyong Du, and Hui Sun
Page(s):  769 - 786

5. Dynamical Models of Stock Prices Based on Technical Trading Rules Part I: The Models
Author(s):  Li-Xin Wang
Page(s):  787 - 801

6. Fuzzy (c + p)-Means Clustering and Its Application to a Fuzzy Rule-Based Classifier: Toward Good Generalization and Good Interpretability
Author(s):  Jacek M. Leski
Page(s):  802 - 812

7. Minimax Probability TSK Fuzzy System Classifier: A More Transparent and Highly Interpretable Classification Model
Author(s):  Zhaohong Deng, Longbing Cao, Yizhang Jiang, and Shitong Wang
Page(s):  813 - 826

8. Stability Analysis of T–S Fuzzy Control Systems by Using Set Theory
Author(s):  Jiuxiang Dong, Guang-Hong Yang, and Huaguang Zhang
Page(s):  827 - 841

9. On the Transformation of Fuzzy Measures to the Power Set and Its Role in Determining the Measure of a Measure
Author(s):  Ronald R. Yager, and Radko Mesiar
Page(s):  842 - 849

10. Clustering Granular Data and Their Characterization With Information Granules of Higher Type
Author(s):  Adam Gacek, and Witold Pedrycz
Page(s):  850 - 860

11. Evolving Fuzzy-Model-Based Design of Experiments With Supervised Hierarchical Clustering
Author(s):  Igor Skrjanc
Page(s):  861 - 871

12. On the Choice of the Pair Conjunction–Implication Into the Fuzzy Morphological Edge Detector
Author(s):  Manuel Gonzalez-Hidalgo, Sebastia Massanet, Arnau Mir, and Daniel Ruiz-Aguilera
Page(s):  872 - 884

13. A Parameterized Nonlinear Programming Approach to Solve Matrix Games With Payoffs of I-Fuzzy Numbers
Author(s):  Deng-Feng Li and Jia-Cai Liu
Page(s):  885 - 896

14. An Inexact Probabilistic–Possibilistic Optimization Framework for Flood Management in a Hybrid Uncertain Environment
Author(s):  Shuo Wang, Guohe Huang, and Brian W. Baetz
Page(s):  897 - 908

15. Principal-Agent Problems Based on Credibility Measure
Author(s):  Xiaoli Wu, Ruiqing Zhao, and Wansheng Tang
Page(s):  909 - 922

16. Evolving Granular Fuzzy Model-Based Control of Nonlinear Dynamic Systems
Author(s):  Daniel Leite, Member, Reinaldo M. Palhares, Victor C. S. Campos, and Fernando Gomide
Page(s):  923 - 938

17. Firing Fuzzy Rules With Measure Type Inputs
Author(s):  Ronald R. Yager
Page(s):  939 - 949

18. Ensuring the Centroid of an Interval Type-2 Fuzzy Set
Author(s):  Maowen Nie, and Woei Wan Tan
Page(s):  950 - 963

19. A Numerical-Integration-Based Simulation Algorithm for Expected Values of Strictly Monotone Functions of Ordinary Fuzzy Variables
Author(s):  Xiang Li
Page(s):  964 - 972

20. A Compact Evolutionary Interval-Valued Fuzzy Rule-Based Classification System for the Modeling and Prediction of Real-World Financial Applications With Imbalanced Data
Author(s):  Jose Antonio Sanz, Dario Bernardo, Francisco Herrera, Humberto Bustince, and Hani Hagras
Page(s):  973 - 990

21. A Self-Tuning zSlices-Based General Type-2 Fuzzy PI Controller
Author(s):  Tufan Kumbasar, and Hani Hagras
Page(s):  991 - 1013

22. Interval Type-2 Fuzzy Set Reconstruction Based on Fuzzy Information-Theoretic Kernels
Author(s):  Hooman Tahayori, Lorenzo Livi, Alireza Sadeghian, and Antonello Rizzi
Page(s):  1014 - 1029

23. Characterizing Compactness of Geometrical Clusters Using Fuzzy Measures
Author(s):  Gleb Beliakov, Gang Li, Huy Quan Vu, and Tim Wilkin
Page(s):  1030 - 1043

24. Decentralized Fuzzy Control of Multiple Cooperating Robotic Manipulators With Impedance Interaction
Author(s):  Zhijun Li, Chenguang Yang, Chun-Yi Su, Shuming Deng, Fuchun Sun, and Weidong Zhang
Page(s):  1044 - 1056

25. The Notion of Weak-Contradiction: Definition and Measures
Author(s):  Humberto Bustince, Nicolas Madrid, and Manuel Ojeda-Aciego
Page(s):  1057 - 1069

26. A Hybrid Neuro-Fuzzy Network Based on Differential Biogeography-Based Optimization for Online Population Classification in Earthquakes
Author(s):  Yu-Jun Zheng, Hai-Feng Ling, Sheng-Yong Chen, and Jin-Yun Xue
Page(s):  1070 - 1083

27. Indirect Adaptive Type-2 Fuzzy Impulsive Control of Nonlinear Systems
Author(s):  Yimin Li, Yuanyuan Sun, Jing Hua, and Li Li
Page(s):  1084 - 1099

28. Output-Feedback Control for T–S Fuzzy Delta Operator Systems With Time-Varying Delays via an Input–Output Approach
Author(s):  Hongyi Li, Yabin Gao, Peng Shi, and Xudong Zhao
Page(s):  1100 - 1112

29. Adaptive Robust Control for Fuzzy Mechanical Systems: Constraint-Following and Redundancy in Constraints
Author(s):  Qingmin Huang, Ye-Hwa Chen, and Aiguo Cheng
Page(s):  1113 - 1126

30. Dynamical Models of Stock Prices Based on Technical Trading Rules—Part II: Analysis of the Model
Author(s):  Li-Xin Wang
Page(s):  1127 - 1141

31. Least-Squares Regression Based on Atanassov’s Intuitionistic Fuzzy Inputs–Outputs and Atanassov’s Intuitionistic Fuzzy Parameters
Author(s):  Mohsen Arefi and Seyed Mahmoud Taheri
Page(s):  1142 - 1154

32. On T-Norms for Type-2 Fuzzy Sets
Author(s):  Pablo Hernandez, Susana Cubillo, and Carmen Torres-Blanc
Page(s):  1155 - 1163

33. Deviation Square Priority Method for Distinct Preference Structures Based on Generalized Multiplicative Consistency
Author(s):  Zeshui Xu
Page(s):  1164 - 1180

34. A Certainty-Based Model for Uncertain Databases
Author(s):  Olivier Pivert and Henri Prade
Page(s):  1181 - 1196

35. H∞ Fuzzy Control Synthesis for a Large-Scale System With a Reduced Number of LMIs
Author(s):  Wei Chang and Wen-June Wang
Page(s):  1197 - 1210

36. Framework of Group Decision Making With Intuitionistic Fuzzy Preference Information
Author(s):  Huchang Liao, Zeshui Xu, Xiao-Jun Zeng, and Jose M. Merig ´ o
Page(s):  1211 - 1227

37. Observer-Based Adaptive Fuzzy Tracking Control of MIMO Stochastic Nonlinear Systems With Unknown Control Directions and Unknown Dead Zones
Author(s):  Yongming Li, Shaocheng Tong, and Tieshan Li
Page(s):  1228 - 1241

38. Fuzzy and Crisp Recursive Profiling of Online Reviewers and Businesses
Author(s):  Pawan Lingras and Matt Triff
Page(s):  1242 - 1258

39. Overlap Indices: Construction of and Application to Interpolative Fuzzy Systems
Author(s):  Santiago Garcia-Jimenez, Humberto Bustince, Eyke Hullermeier, Radko Mesiar, Nikhil R. Pal, and Ana Pradera
Page(s):  1259 - 1273

40. Pinning Synchronization in T–S Fuzzy Complex Networks With Partial and Discrete-Time Couplings
Author(s):  Chi Huang, Daniel W. C. Ho, Jianquan Lu, and Jurgen Kurths
Page(s):  1274 - 1285

41. Speedup of Learning in Interval Type-2 Neural Fuzzy Systems Through Graphic Processing Units
Author(s):  Chia-Feng Juang, Wei-Yuan Chen, and Chung-Wei Liang
Page(s):  1286 - 1298

42. Weighting the Support Conjectures Inherit From Premises
Author(s):  Enric Trillas, Claudio Moraga, and Gracian Trivino
Page(s):  1299 - 1305

43. Stancu OWA Operator
Author(s):  Amit K. Singh, Amar Kishor, and Nikhil R. Pal
Page(s):  1306 - 1313

44. Stability Analysis and Region-of-Attraction Estimation Using Piecewise Polynomial Lyapunov Functions: Polynomial Fuzzy Model Approach
Author(s):  Ying-Jen Chen, Motoyasu Tanaka, Kazuo Tanaka, and Hua O. Wang
Page(s):  1314 - 1322

45. Stability of Fuzzy Differential Equations With the Second Type of Hukuhara Derivative
Author(s):  Shuorui Zhang and Jitao Sun
Page(s):  1323 - 1328

Webinar Competition Call for Submissions

IEEE CIS invites students and young professionals (those within fifteen years from their first degree) to submit their entries to the 2015 Webinar Competition. The aim of the webinar will be to explain either a real world application of computational intelligence or an emerging topic in computational intelligence. Submissions are in two phases:

• Phase 1: the participants should submit the title and abstract of their intended webinars. The abstract should contain no more than 500 words.
• Phase 2: shortlisted participants will prepare a 30-min talk and submit it to YouTube.

Prizes

1st Place: 500 USD
2nd Place: 300 USD
3rd Place: 200 USD
The IEEE CIS reserves the right to award less than three prizes, including no prize, should that be judged appropriate. The decisions made by the competition organizing committee are final.

Each prize winner will also receive an official IEEE Computational Intelligence Society prize certificate.

Important Dates

Phase 1 deadline: 10th August 2015 24th August 2015
Phase 2 deadline: 30th August 2015 13th September 2015

Judgement criteria for shortlisting and selecting the winners of the competition

• Novelty of the real world application or the emerging topic being explained
• Soundness
• Relevance (there should be a clear justification of why the entry can be considered an emerging topic or a real world application of computational intelligence)
• Popularity (number of “likes” vs “dislikes” and comments in YouTube) – note that these will be counted only until 27th September 2015
• Presentation and clarity

 

Eligibility

The submission must be made by a single author who must be over the age of 18 (under 18s must provide parental consent).
Proof that the author qualifies as a student or young professional at the deadline of phase 1 should be provided. This will be a letter from the University confirming that the author is a student, a BSc diploma, or equivalent.

Winners must sign a video collection form giving IEEE the right to include their video at the IEEE CIS Education Website.

Format

Phase 1: abstract submissions should be in English. The abstract should have no more than 500 words.
Phase 2: videos must be narrated in English and be available through YouTube. The video should take no more than 30 min. At the beginning of the video, a disclaimer of "This video is submitted to the Webinar Competition 2015 supported by IEEE CIS" should be shown.

Submission

Phase 1: submit your title + abstract at
https://easychair.org/conferences/?conf=webicomp2015

Phase 2: submit the link to your YouTube video at the beginning of your abstract at
https://easychair.org/conferences/?conf=webicomp2015

Organization

• IEEE CIS
• Webinars Subcommittee
• Student Subcommittee
• Young Professionals Subcommittee
• Education Committee

Albert Lam <ayslam@gmail.com>
Leandro Minku <L.L.Minku@cs.bham.ac.uk>
Manuel Roveri <manuel.roveri@polimi.it>

Call for Papers WCCI 2016 Special Session: Evolutionary Feature Selection and Construction

Many data mining and machine learning problems involve a large number of features/attributes, which leads to "the curse of dimensionality". However, not all the features are essential since many of them are redundant or even irrelevant, and the "useful" features are typically not equally important. This problem can be solved by feature selection to select a small subset of original (relevant) features or feature construction to create a smaller set of high-level features using the original low-level features and mathematical or logical operators. Feature selection and construction are challenging tasks due to the large search space and feature interaction problems. Recently, there has been increasing interest in using evolutionary computation techniques to solve feature selection and construction tasks.

The theme of this special session is the use of evolutionary computation for feature reduction, covering ALL different evolutionary computation paradigms, including Genetic algorithms (GAs), Genetic programming (GP), Evolutionary programming (EP), Evolution strategies (ES), Learning classifier systems (LCS), Particle swarm optimization (PSO), Ant colony optimization (ACO), Differential evolution (DE), Artificial immune systems (AIS), Evolutionary Multi-objective optimization (EMO), Estimation of distribution algorithms (EDA), and Cultural algorithms (CA).

The aim is to investigate both the new theories and methods in different evolutionary computation paradigms to feature reduction, and the applications of evolutionary computation for feature reduction. Authors are invited to submit their original and unpublished work to this special session. Topics of interest include but are not limited to:

• Feature ranking/weighting
• Feature subset ranking
• Feature subset selection
• Filter, wrapper, and embedded methods for feature selection
• Multi-objective feature selection
• Feature construction/extraction
• Single feature or multiple features construction
• Filter, wrapper, and embedded methods for feature construction
• Multi-objective feature construction
• Analysis on evolutionary feature selection and construction algorithms
• Feature selection and construction in classification, clustering, regression, and other tasks
• Feature selection and construction on high-dimensional and large-scale data
• Hybridisation of evolutionary computation and neural networks, and fuzzy systems for feature selection and construction
• Hybridisation of evolutionary computation and machine learning, information theory, statistics, mathematical modelling, etc., for feature selection and construction
• Real-world applications of evolutionary feature selection and construction, e.g. images and video sequences/analysis, face recognition, gene analysis, biomarker detection, medical data classification, diagnosis, and analysis, hand written digit recognition, text mining, instrument recognition, power system, financial and business data analysis, et al.

 

Important dates:

15 Nov 2015 Special Session & Workshop Proposals Deadline
15 Dec 2015 Competition & Tutorial Proposals Deadline
15 Jan 2016 Paper Submission Deadline
15 Mar 2016 Paper Acceptance and Notification Date
15 Apr 2016 Final Paper Submission and Early Registration Deadline
25-29 Jul 2016 IEEE WCCI 2016 Vancouver, Canada

Paper Submission:

Please follow the IEEE WCCI/CEC 2016 Submission Web Site. Special session papers are treated the same as regular conference papers. Please specify that your paper is for the Special Session on Evolutionary Feature Selection and Construction. All papers accepted and presented at WCCI/CEC 2016 will be included in the conference proceedings published by IEEE Explore, which are typically indexed by EI.

Organizers:

Bing Xue
School of Engineering and Computer Science, Victoria University of Wellington, PO Box 600, Wellington, New Zealand.
Bing.Xue@ecs.vuw.ac.nz
Phone: +64-4-463 5233+8874; Fax: +64-4-463 5045.

Yaochu Jin
Department of Computing, University of Surrey, United Kingdom.
yaochu.jin@surrey.ac.uk
Phone: +44-1483-686037; Fax: +44-1483-686051

Mengjie Zhang
School of Engineering and Computer Science, Victoria University of Wellington, PO Box 600, Wellington, New Zealand.
Mengjie.Zhang@ecs.vuw.ac.nz
Phone: +64-4-463 5654; Fax: +64-4-463 5045

Biography of the Organizers

Bing Xue is currently a Lecturer in Evolutionary Computation Research Group, School of Engineering and Computer Science at Victoria University of Wellington and leading the strategic research direction on evolutionary feature selection and construction. Her research focuses mainly on evolutionary computation, feature selection, feature construction, multi-objective optimisation, data mining and machine learning. She has over 40 papers published in fully referred international journals and conferences and 30 of them are on evolutionary feature selection and construction. She is currently co-supervising six PhD students and visiting scholars, and over 10 Honours and summer research projects. Dr Xue is the chair of the special session on Evolutionary Feature Selection and Construction in IEEE Congress on Evolutionary Computation (CEC) 2015 and the chair of the special session on Evolutionary Feature Reduction in the international conference on Simulated Evolution And Learning (SEAL) 2014. She is a Guest Editor for the Special Issue on Evolutionary Feature Reduction and Machine Learning for the Springer Journal of Soft Computing. Dr Xue is serving as a reviewer of over 10 international journals including IEEE Transactions on Evolutionary Computation, IEEE Transaction on Cybernetics and Information Sciences, and many international conferences including IEEE Congress on Evolutionary Computation (CEC), International Joint Conference on Artificial Intelligence (IJCAI), Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), and International Conference on Simulated Evolution and Learning (SEAL). Dr Xue is a member of IEEE and IEEE Computational Intelligence Society. She is also serving as the Director of Women in Engineering for the IEEE New Zealand Central Section and the Secretary of the IEEE Chapter on Computational Intelligence in that Section.

Yaochu Jin received the B.Sc., M.Sc., and Ph.D. degrees from Zhejiang University, Hangzhou, China, in 1988, 1991, and 1996 respectively, and the Dr. Ing. degree from Ruhr-University Bochum, Bochum, Germany, in 2001. Dr Jin is a Professor and the Chair in Computational Intelligence with the Department of Computing, University of Surrey, Guildford, U.K., where he heads the Nature Inspired Computing and Engineering Group. His science-driven research interests lie in interdisciplinary areas that bridge the gap between computational intelligence, computational neuroscience, and computational systems biology. He is also particularly interested in nature-inspired, real-world driven problem-solving, such as aerodynamic optimisation, natural gas terminal design, intelligent heating systems, and process optimisation and control. Recently, he has also been carrying out research in feature extraction and construction in images.
Dr Jin has (co)edited five books and three conference proceedings, authored a monograph, and (co)authored over 150 peer-reviewed journal and conference papers. He has been granted eight US, EU and Japan patents. His current research is funded by EC FP7, UK EPSRC and industries, including Airbus, Bosch UK, HR Wallingford and Honda. He has delivered 16 invited keynote speeches at international conferences. He is an Associate Editor/Editorial Board Member of IEEE Transactions on Cybernetics, IEEE Transactions on NanoScience, and IEEE Computational Intelligence Magazine, Evolutionary Computation (MIT), BioSystems (Elsevier) and Soft Computing (Springer). He is a past Associate Editor of IEEE Transactions on Neural Networks, IEEE Transactions on Systems man and Cybernetics, Part C, and IEEE Transactions on Control Systems Technology. Dr Jin is currently an IEEE Distinguished Lecturer, Vice President for Technical Activities and an AdCom Member of the IEEE Computational Intelligence Society. He was the recipient of the Best Paper Award of the 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. He is a Fellow of BCS and Senior Member of IEEE.

Mengjie Zhang is currently Professor of Computer Science at Victoria University of Wellington, where he heads the interdisciplinary Evolutionary Computation Research Group. He is a member of the University Academic Board, a member of the University Postgraduate Scholarships Committee, a member of the Faculty of Graduate Research Board at the University, Associate Dean (Research and Innovation) for Faculty of Engineering, and Chair of the Research Committee of the Faculty and School of Engineering and Computer Science. His research is mainly focused on evolutionary computation, particularly genetic programming, particle swarm optimization, multi-objective optimization and learning classifier systems with application areas of classification with unbalanced data, feature selection and dimensionality reduction, computer vision and image processing, job shop scheduling, and bioinformatics. He is also interested in data mining, machine learning, and web information extraction. Prof Zhang has published over 300 academic papers in refereed international journals and conferences in these areas. He has been serving as an associated editor or editorial board member for five international journals including IEEE Transactions on Evolutionary Computation, the Evolutionary Computation Journal (MIT Press) and Genetic Programming and Evolvable Machines (Springer), and as a reviewer of over 20 international journals. He has been a general/program/technical chair for eight international conferences. He has also been serving as a steering committee member and a program committee member for over 100 international conferences including all major conferences in evolutionary computation. Since 2007, he has been listed as one of the top ten world genetic programming researchers by the GP bibliography (http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/index.html). Prof Zhang is a senior member of IEEE, Chair of the IEEE CIS Evolutionary Computation Technical Committee, a member of IEEE CIS Intelligent System Applications Technical Committee, a vice-chair of the IEEE CIS Task Force on Evolutionary Computer Vision and Image Processing, and the founding chair of the IEEE Computational Intelligence Chapter in the IEEE New Zealand Central Section.

Call for Papers WCCI 2016 Special Session: Evolutionary Computer Vision

Organized by Mengjie Zhang, Vic Ciesielski and Mario Koppen

Overview

Computer vision is a major unsolved problem in computer science and engineering. Over the last decade there has been increasing interest in using evolutionary computation approaches to solve vision problems. Computer vision provides a range of problems of varying difficulty for the development and testing of evolutionary algorithms. There have been a relatively large number of papers in evolutionary computer vision in recent CEC and GECCO conferences. It would be beneficial to researchers to have these papers in a special session. Also, a special session would encourage more researchers to continue to work in this field and consider CEC a place for presenting their work.

Scope and Topics

The proposed special session aims to bring together theories and applications of evolutionary computation to computer vision and image processing problems. Topics of interest include, but are not limited to:

New theories and methods in different EC paradigms to computer vision and image processing including

• Evolutionary algorithms such as Genetic algorithms, genetic programming, evolutionary strategy and evolutionary programming;
• Swarm Intelligence such as particle swarm optimisation, ant colony optimisation, and differential evolution; and
• Other approaches such as learning classifier systems, harmony search, and artificial immune systems. Cross-fertilization of evolutionary computation and other techniques such as neural networks and fuzzy systems is also encouraged.

Applications in computer vision and image processing including

• Edge detection in noisy images
• Image segmentation in biological images
• Automatic feature extraction, construction and selection in complex images
• Object identification and scene analysis for medical applications
• Object detection and classification in security scenarios
• Handwritten digit recognition and detection
• Vehicle plate detection
• Face detection and recognition
• Texture image analysis
• Automatic target recognition in military services
• Gesture identification and recognition
• Robot vision

Submission

Please follow the IEEE CEC2016 instruction for authors and submit your paper via the IEEE CEC 2016 online submission system. Please specify that your paper is for the Special Session on Evolutionary Computer Vision.

Important Dates:

• Paper Submission Deadline: 15 Jan 2016
• Notification of Acceptance: 15 Mar 2016
• Final Paper Submission Deadline: 15 Apr 2016

Special Session Organizers:

Mengjie Zhang, School of Engineering and Computer Science, Victoria University of Wellington, PO Box 600, Wellington, New Zealand.

Email: mengjie.zhang@ecs.vuw.ac.nz

Homepage: http://homepages.ecs.vuw.ac.nz/~mengjie/

Mengjie Zhang is Professor of computer science at Victoria University of Wellington, New Zealand, where he is heading the interdisciplinary Evolutionary Computation Research Group. He has been working in the area of evolutionary computer vision and signal processing for over 10 years. He has over 350 publications in international conferences and journals including over 100 in evolutionary computer vision and has been supervising over 50 research students in this area. He is currently the Chair of IEEE CIS Evolutionary Computation Technical Committee, a member of IEEE CIS Intelligent Systems and Application Technical Committee, an Associate Editor or Editorial Board for six international journals including IEEE Transactions on Evolutionary Computation, the Evolutionary Computation Journal (MIT Press) and Genetic Programming and Evolvable Machines (Springer). He is also a Vice-Chair of the IEEE CIS Task Force on Evolutionary computer vision and image processing, a Vice-Chair of the IEEE CIS Task Force on Evolutionary Feature Selection and Construction, and the founding Chair of the IEEE Chapter on Computational Intelligence in New Zealand (Central Section).

Vic Ciesielski, School of Computer Science and Information Technology, RMIT University, City Campus, GPO 2476V, VIC, Australia.

Email: vic.ciesielski@cs.rmit.edu.au

Homepage: http://www.cs.rmit.edu.au/~vc/

Vic Ciesielski is an Associate Professor of computer science at RMIT University. He has been working in the area of evolutionary computer vision for over 10 years. He has over 100 publications in international conferences and journals including more than 40 on various aspects of evolutionary computer vision. He has supervised six PhD students in this area. He is also a member of the Task Force on Evolutionary Computer Vision and Image Processing (IEEE CIS EC Technical Committee).

Mario Koeppen, Graduate School of Creative Informatics, Kyushu Institute of Technology, 680-4, Kawazu, Iizuka, Fukuoka 820-8502 JAPAN.

Email: mkoeppen@ieee.org

Homepage: http://science.mkoeppen.com/

Mario Köppen is a professor at Kyuhsu Institute of Technology, Japan. He has also been working in the field of applied image processing within the scope of industrial projects for more than ten years. His research is focused on the use of soft computing technologies, esp. evolutionary computation, neural networks and fuzzy fusion, for the design of image processing applications. He has over 150 publications in international conferences, journals and book chapters, including a large number of publications that are strongly related to the topic of this proposal. He is also a Vice-Chair of the Task Force on Evolutionary computer vision and image processing (IEEE CIS EC Technical Committee).

Call for Papers WCCI 2016 Special Session: Evolutionary Computation and Other Computational Intelligence Techniques for Cyber Security

Overview

The Internet of Things (IoT) and our cyber–physical environment bring great benefits by connecting People, Processes and Data. They offer an easier, safer, smarter, more productive and more prosperous lifestyle for everyone. Whether it is smart, connected homes caring for their elderly residents, driverless vehicles improving transport safety and efficiency or wearable personal medical technology, our cyber-enabled future looks bright. However, great opportunities also bring large risks. Cyber-enabled systems can be threatened by a wide variety of cyber-attacks from criminals, terrorists and hacktivists. As a consequence, cyber security is particularly important for cyber–physical systems, with the public and senior decision-makers becoming ever more aware of the dangers caused by the malicious exploitation of poorly-secured systems.

Evolutionary Computation and other Computational Intelligence techniques (EC&CI) have been successfully applied in various areas, such as computational biology, medical science, finance, engineering, etc. Cyber security is a key area where we can exploit the power of EC&CI. The importance of this special session is that, unlike other problem domains, the design of intelligent solutions for cyber security has to be resilient in the face of determined, sophisticated attackers who will target any adaptive system. Often, we see that it is the adaptive parts of a system – intelligent anti-virus or intrusion detection systems, adaptive network protocols, dynamic web content – that offer the best opportunities for an attacker. We hope that intelligent cyber security can secure the benefits to all from our cyber-connected world, and that our research, combining EC&CI with cyber security, will underpin our safe, secure and prosperous connected future..

Topics of Interest

This special session presents the latest research in EC&CI for cyber security, promoting an exchange of new ideas and exploring the potential of EC&CI techniques for cyber security. Original contributions that provide novel theories, techniques, architectures and solutions to challenging problems related to cyber security are very welcome for this Special Session. Potential topics include, but are not limited to:

1. Bio-inspired cyber security architectures
2. Adaptive cloud security
3. Intelligent defences against privacy-invading technologies
4. Biometrics and evolutionary authentication
5. Insider threat detection
6. Prediction of attacks
7. Smart systems for risk management
8. Detection and analysis of malware 
9. Autonomous Security
10. Information and process security
11. Privacy and anonymity enhancing techniques
12. Adaptive, secure protocols

Submission

Please follow the IEEE CEC2016 instruction for authors and submit your paper via the IEEE CEC 2016 online submission system. Please specify that your paper is for the Special Session on Evolutionary Computation and Other Computational Intelligence Techniques for Cyber Security.

Important Dates

Paper Submission Deadline:    15 Jan 2016
Notification of Acceptance:    15 Mar 2016
Final Paper Submission Deadline:    15 Apr 2016

Organisers

Dr Hongmei He, Cranfield University, UK, h.he@cranfield.ac.uk
Professor Ashutosh Tiwari, Cranfield University, UK,  A.Tiwari@cranfield.ac.uk
Dr Jorn Mehnen, Cranfield University, j.mehnen@cranfield.ac.uk
Professor Tim Watson, University of Warwick, UK, tw@warwick.ac.uk
Professor Yaochu Jin, University of Surrey, yaochu.jin@surrey.ac.uk
Professor Bogdan Gabrys, University of Bournemouth, BGabrys@bournemouth.ac.uk

Biography of the Proposers

Dr Hongmei He is a lecturer in Cyber-Security for Manufacturing and Information Intelligence in the Manufacturing Informatics Centre at Cranfield University. She was awarded a PhD degree in Computer Science and MSc degree in Multimedia and Internet Computing by Loughborough University in 2006 and 2003 respectively. Dr He’s research focused on Computational Intelligence for a wide range of applications, such as data/information fusion, network-based data mining, non-linear regression, cognitive robotics, identification and wireless sensor networks. Recently, she put much attention on Cyber Security, and developed a new MSc course in Cyber Secured Manufacturing Informatics. She is particularly interested in data/information driven cyber security, and try to apply computational intelligence, in particular, bioinspired approaches for computer security, authentication and prediction of cyber attacker’s behaviour, capacity and intents. She has published more than 40 papers in peer-reviewed journals and international conferences since 2004. Dr He has been an Editorial Board Member of Advances in Computing since 2011, the member of IEEE (Computer Science, Computational Intelligence, Cyber Security and Robotics societies) since 2005, and a representative of IEEE Ireland section since 2009. She also served as a committee member or session chair for some international conferences, such as IJCNN2015, IAENG ICAIA'09, WCCI2008, etc.

Professor Ashutosh Tiwari is Chair in Manufacturing Informatics and Head of the Manufacturing Informatics Centre at Cranfield University. His research focuses on the digitisation, simulation and optimisation of high-value manufacturing processes, such as wing manufacture and engine assembly. His current research has investigated the cyber security implications of advancements in manufacturing informatics. He is a fellow of the Institution of Mechanical Engineers (IMechE), a fellow of the Institution of Engineering and Technology (IET), a fellow of the Higher Education Academy, treasurer of the World Federation on Soft Computing (WFSC) and steering committee member of the NAFEMS Optimisation Working Group. He has produced 236 research publications including 93 refereed journal papers, 93 refereed conference papers and 50 book chapters, edited books and workshop papers. He was awarded the IMechE Thatcher Bros Prize 2008/09 for the best journal paper in manufacturing. He is an associate editor of the International Journal of Design Engineering, a survey/review article editor of the Applied Soft Computing Journal, and an editorial board member of the IMechE Journal of Engineering Manufacture.

Dr Jorn Mehnen is Reader in Computational Manufacturing at Cranfield University, UK.  He is also Deputy Director of the EPSRC Centre for Innovative Manufacturing in Through-life Engineering Services and Privatdozent at TU Dortmund, Germany. His expertise lies in the area of the application of Computer Science technologies to manufacturing through utilizing latest technology such as Cloud Manufacturing, Through Life Services Engineering and Evolutionary Computation.  Dr Mehnen is co-editor of the renowned CI journal Applied Soft Computing and regular co-organiser of the Evolutionary Computation in Practice track at GECCO. Dr Mehnen is author of 4 books, 13 book chapters, 32 top ranked journals and 57 proceedings papers.

Professor Tim Watson is the Director of the Cyber Security Centre at WMG within the University of Warwick. He is an advisor to various parts of the UK government and to several professional and standards bodies. Tim's current research includes EU funded projects on combating cyber-crime, UK MoD research into automated defence, insider threat and secure remote working, and research into the protection of infrastructure against cyber-attack. He is the Vice President (Academia) of the Trustworthy Software Initiative, a UK government sponsored project and a key deliverable of the UK National Cyber Security Programme. Tim was recently the Chair of the European Information Security Summit 2015 and is on the advisory board of the Journal of Cybersecurity. Tim is also a regular media commentator on digital forensics and cyber security.

Professor Yaochu Jin (M’98–SM’02) is a Professor in Computational Intelligence with the Department of Computer Science, University of Surrey, Guildford, UK, where he is the Head of the Nature Inspired Computing and Engineering Group. He is also a Finland Distinguished Professor awarded by Finnish Funding Agency for Innovation and Changjiang Distinguished Visiting Professor appointed by Ministry of Education, China. Prof Jin has (co)edited five books and three conference proceedings, authored a monograph, and (co)authored over 150 peer-reviewed journal and conference papers. He has been granted eight US, EU and Japan patents. His current research is funded by EC FP7, UK EPSRC and industries, including Airbus, Bosch UK, HR Wallingford and Honda. He has delivered 20 invited keynote speeches at international conferences.

Prof Jin is an Associate Editor or Editorial Board Member of IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, IEEE TRANSACTIONS ON CYBERNETICS, IEEE TRANSACTIONS ON NANOBIOSCIENCE, IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS and IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, Evolutionary Computation (MIT), BioSystems (Elsevier), Natural Computing (Springer), and Soft Computing (Springer).  Dr Jin is currently an IEEE Distinguished Lecturer and Vice President for Technical Activities of the IEEE Computational Intelligence Society. He was the recipient of the 2014 IEEE Computational Intelligence Magazine Outstanding Paper Award and the Best Paper Award of the 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. He is a Fellow of British Computer Society and Senior Member of IEEE.

Professor Bogdan Gabrys is a professor in Computational Intelligence at Bournemouth University (BU) since January 2003. He has founded and acted as a Director of Data Science Institute (2014- present), Smart Technology Research Centre (2007 - 2014) and Computational Intelligence Research Group (2003 - present) all hosted within the Faculty of Science and Technology at BU. His current research interests lay in a broad area of intelligent and biologically/nature inspired learning and complex adaptive systems and include a wide range of machine learning and hybrid intelligent techniques encompassing data and information fusion, learning and adaptation methods, multiple classifier and prediction systems, complex adaptive systems, processing and modelling of uncertainty in predictive analytics, pattern recognition, diagnostic analysis and decision support systems.
Among others, Prof Gabrys acts as the Chair (Academic Affairs) of KES International and is a Co-Editor in Chief of the International Journal of Knowledge Based & Intelligent Engineering Systems. He was co-ordinating a recently completed EU funded INFER project (http://www.infer.eu) focusing on robust adaptive predictive systems, a topic which is relevant to this special session. In the past he was a co-chairman of the Nature-inspired Data Technology focus group within an EU funded Coordination Action project on Nature-inspired Smart Information Systems (NiSIS). He was also a corresponding person for a Key Node in the European Network of Excellence on Intelligent Technologies for Smart Adaptive Systems (EUNITE) and a co-chairman of the Research Theory & Development Group on Integration of Methods. More information can be found at his personal web page: http://dec.bournemouth.ac.uk/staff/bgabrys/.

Call for Papers WCCI 2016 Special Session: Computational Intelligence in Aerospace Science and Engineering

Scope and Motivations

In an expanding world with limited resources and increasing complexity, optimisation and computational intelligence become a necessity. Optimisation can turn a problem into a solution and computational intelligence can offer new solutions to effectively make complexity manageable. All this is particularly true in space and aerospace where complex systems need to operate optimally often in harsh and inhospitable environment with high level of reliability.  In Space and Aerospace Sciences, many applications require the solution of global single and/or multi-objective optimization problems, including mixed variables, multi-modal and non-differentiable quantities. From global trajectory optimization to multidisciplinary aircraft and spacecraft design, from planning and scheduling for autonomous vehicles to the synthesis of robust controllers for airplanes or satellites, computational intelligence (CI) techniques have become an important – and in many cases inevitable – tool for tackling these kinds of problems, providing useful and non-intuitive solutions. Not only have Aerospace Sciences paved the way for the ubiquitous application of computational intelligence, but moreover, they have also led to the development of new approaches and methods.

Session Topics

This special session intends to collect many, diverse efforts made in the application of computational intelligence techniques, or related methods, to aerospace problems. The session seeks to bring together researchers from around the globe for a stimulating discussion on recent advances in evolutionary methods for the solution of space and aerospace problems.  Authors are invited to submit papers on one or more of the following topics:

• Global trajectory optimization
• Multidisciplinary design for space missions
• Formation and constellation design and control
• Optimal control of spacecraft and rovers
• Planning and scheduling for autonomous systems in space
• Multiobjective optimization for space applications
• Resource allocation and programmatics
• Evolutionary computation for Concurrent Engineering
• Distributed global optimization
• Mission planning and control
• Robust Mission Design under Uncertainties
• Intelligent search and optimization methods in aerospace applications
• Image analysis for Guidance Navigation and Control
• Autonomous exploration of interplanetary and planetary environments
• Emerging AI technologies and Swarm Intelligence 
• Intelligent algorithms for fault identification, diagnosis and repair
• Multi-agent systems and bio-inspired solutions for system design and control
• Advances in machine learning for space applications
• Intelligent interfaces for human-machine interaction
• Knowledge Discovery, Data Mining and presentation of large data sets

Submission Guidelines

Manuscripts should be prepared according to the standard format of regular papers specified in IEEE WCCI2016. Paper submission is online through the WCCI2016 submission website http://www.wcci2016.org/submission.php  Papers submitted for these session will be peer-reviewed with the same criteria used for other contributed papers. All accepted papers in the special sessions will be included in the published conference proceedings.

Post Conference Publication

Selected high-quality papers will be recommended for publication in the International Journal of Intelligent Computing and Cybernetics (IJICC)  after extension.

Important Dates

Paper Submission:
15 January 2016

Decision Notification:
15 April 2016

Camera-Ready Submission:
13 March 2015

Session Organisers

Prof. Massimiliano Vasile
Department of Mechanical & Aerospace Engineering
University of Strathclyde, Glasgow, UK
massimiliano.vasile@strath.ac.uk

Dr. Chit Hong Yam
Institute of Space and Astronautical Science
Japan Aerospace Exploration Agency
Sagamihara, Japan
chithong.yam@ac.jaxa.jp

Prof. Victor Becerra
School of Systems Engineering
University of Reading
v.m.becerra@reading.ac.uk

Dr. Edmondo Minisci
Department of Mechanical & Aerospace Engineering
University of Strathclyde, Glasgow, UK
edmondo.minisci@strath.ac.uk

Dr. Annalisa Riccardi
Department of Mechanical & Aerospace Engineering
University of Strathclyde, Glasgow, UK
Annalisa.riccardi@strath.ac.uk