Thursday, 31 December 2015

Call for Papers WCCI/IJCNN 2016 Special Session: Deep Learning for Brain-Like Computing and Pattern Recognition

Deep learning is a topic of broad interest, both to researchers who develop new deep architectures and learning algorithms, as well as to practitioners who apply deep learning models to a wide range of applications, from image classification to video tracking, etc. Brainlike computing combines computational techniques with cognitive ideas, principles and models inspired by the brain for building information systems used in humans’ common life. Pattern recognition is a conventional area of artificial intelligence, which focuses on the recognition of patterns and regularities in data. Recently, there has been very rapid and impressive progress in these three areas, in terms of both theories and applications, but many challenges remain. This special session aims at bringing together researchers in machine learning and related areas to discuss the utility of deep learning for brain-like computing and pattern recognition, the advances, the challenges we face, and to brainstorm about new solutions and directions.

Call for Papers 
Papers for this special session of IJCNN 2016 should be submitted electronically through the Congress website at www.wcci2016.org. Please submit your paper to the special session: Deep Learning for Brain-Like Computing and Pattern Recognition.

We can only accept PDF files. The maximum number of pages is eight (8) and maximum file size is 10MB. Up to two additional pages will be permitted for a charge of USD 100 per additional page payable at the registration time. Illustrations and references are included in the page count. You are responsible for ensuring that your submission is in valid format and that it will be readable and printable. Please double check your file before submitting it.

Important Dates 
Paper Submission 2016-01 -15
Paper Decision Notification 2016-03-15
Camera-ready Submission 2016-04-15
Conference Days 2016-05-25 -- 2016-05-29

Saturday, 26 December 2015

Call for Papers & Call for Tutorials and Special Sessions The Sixth Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics


IEEE ICDL-EPIROB 2016

Cergy-Pontoise / Paris, France September 19-22th, 2016 http://www.icdl-epirob.org

Conference description

The past decade has seen the emergence of a new scientific field that studies how intelligent biological and artificial systems develop sensorimotor, cognitive and social abilities, over extended periods of time, through dynamic interactions with their physical and social environments. This field lies at the intersection of a number of scientific and engineering disciplines including Neuroscience, Developmental Psychology, Developmental Linguistics, Cognitive Science, Computational Neuroscience, Artificial Intelligence, Machine Learning, and Robotics. Various terms have been associated with this new field such as Autonomous Mental Development, Epigenetic Robotics, Developmental Robotics, etc., and several scientific meetings have been established. The two most prominent conference series of this field, the International Conference on Development and Learning (ICDL) and the International Conference on Epigenetic Robotics (EpiRob), are now joining forces for the sixth time and invite submissions for a joint conference in 2016, to explore and extend the interdisciplinary boundaries of this field. 

Others to be confirmed.

Call for Submissions

We invite submissions for this exciting window into the future of developmental sciences. Submissions which establish novel links between brain, behavior and computation are particularly encouraged.

Topics of interest include (but are not limited to):

  • the development of perceptual, motor, cognitive, emotional, social, and communication skills in biological systems and robots; 
  • embodiment; 
  • general principles of development and learning; 
  • interaction of nature and nurture; 
  • sensitive/critical periods; 
  • developmental stages; 
  • grounding of knowledge and development of representations; 
  • architectures for cognitive development and open-ended learning; 
  • neural plasticity; 
  • statistical learning;
  • reward and value systems; 
  • intrinsic motivations, exploration and play; 
  • interaction of development and evolution; 
  • use of robots in applied settings such as autism therapy; 
  • epistemological foundations and philosophical issues. Any of the topics above can be simultaneously studied from the neuroscience, psychology or modeling/robotic point of view.

Submissions will be accepted in several formats:
  1. Full six-page paper submissions: Accepted papers will be included in the conference proceedings and will be selected for either an oral presentation or a featured poster presentation. Featured posters will have a 1 minute "teaser" presentation as part of the main conference session and will be showcased in the poster sessions.
  2. Two-page poster abstract submissions: To encourage discussion of late-breaking results or for work that is not sufficiently mature for a full paper, we will accept 2-page abstracts. These submissions will NOT be included in the conference proceedings. Accepted abstracts will be presented during poster sessions.
  3. Tutorials and workshops: We invite experts in different areas to organize either a tutorial or a workshop to be held on the first day of the conference. Tutorials are meant to provide insights into specific topics as well as overviews that will inform the interdisciplinary audience about the state-of-the-art in child development, neuroscience, robotics, or any of the other disciplines represented at the conference. A workshop is an opportunity to present a topic cumulatively. Workshop can be half- or full-day in duration including oral presentations as well as posters. Submission format: two pages. 

Call for Tutorials and Workshops

We invite experts in different areas to organize a tutorial or workshop, which will be held on the first day of the conference. Participants in tutorials and workshops are asked to register for the main conference. Tutorials are meant to provide insights into specific topics as well as overviews that will inform the interdisciplinary audience about the state-of-the-art in child development, neuroscience, robotics, or any of the other disciplines represented at the conference. A workshop is an opportunity to present a topic cumulatively. Workshop can be half- or full-day in duration including oral presentations as well as posters. 

Submissions (max. two pages) should be sent no later than April 1st, 2016 to:

Verena Hafner hafner@informatik.hu-berlin.de
Sofiane Boucenna sofiane.boucenna@ensea.fr 
Alexandre Pitti alexandre.pitti@ensea.fr

including: 
  • Title of tutorial or workshop; 
  • Tutorial/workshop speaker(s), including short CVs/affiliations and other relevant information; 
  • Concept of the tutorial/workshop; target audience or prerequisites. All proposals submitted will be subjected to a peer review process. 

Important dates

  • April 1st, 2016, paper submission deadline 
  • June 1st, 2016, author notification 
  • July 1st, 2014, final version (camera ready) due 
  • September 19th-22nd, 2014, conference == Program committee

Organizers

General chairs: 

Minoru Asada Osaka (Japan). 
Philippe Gaussier, Cergy-Pontoise (France).

Program chairs: 

Verena Hafner, Berlin (Germany) 
Alexandre Pitti, Cergy-Pontoise (France)

Bridge chairs: 

David Cohen, Paris (France) 
Mathew Schlesinger, Southern Illinois (USA)

Publication chairs: 

Sofiane Boucenna, Cergy-Pontoise (France)

Publicity chairs: 

Arnaud Blanchard, Cergy-Pontoise (France) 
Manuel Lopes, Bordeaux (France) 
Yulia Sandamirskaya, Bochum (Germany)

Local chairs:

Pierre Andry, Cergy-Pontoise (France)
Nicolas Cuperlier, Cergy-Pontoise (France)

Finance chairs:

Ghilès Mostafaoui, Cergy-Pontoise (France)


Thursday, 24 December 2015

Call for Papers Special Session(JCNN-09): Intelligent Vehicle and Transportation Systems

With WCCI 2016, July 25-29, 2016, Vancouver, Canada
The research and development of intelligent vehicles and transportation systems are rapidly growing worldwide. Intelligent transportation systems are making transformative changes in all aspects of surface transportation based on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity. With the decreasing sensor costs and computer chips, and increasing computing power and data storage capacity, it has become practical to build a host of intelligent devices in cars that can be used in airbag control, unwelcome intrusion detection, collision warning and avoidance, power management and navigation, driver alertness monitoring etc. Computational intelligence plays a vital role in building all types and levels of intelligence in vehicle and transportation systems.

The objective of this special session is to provide a forum for researchers and practitioners to present advanced research in computational intelligence with a focus on innovative applications to intelligent vehicle and transportation systems. This session seeks contribution on the latest developments and emerging research in all aspects of intelligent vehicle and transportation systems. Specific topics for the session include, but are not limited to:
  • Advanced transportation information and communication systems
  • Cloud computing and big data in transportation and vehicle systems
  • Multimodal intelligent transport systems and services
  • Personalized driver and traveler support systems
  • Pervasive and ubiquitous computing in logistics
  • Simulation and forecasting models
  • Spatio-temporal traffic pattern recognition
  • Connected vehicles
  • Air, Road, and Rail Traffic Management
  • Advanced Transportation Management
  • Collision detection and avoidance 
  • vehicle communications and connectivity
  • Driver state detection and monitoring
  • Driver assistance and automation systems
  • Vehicle fault diagnostics and health monitoring
  • Automated driving and driverless car
  • Learning and adaptive Control 
  • Object recognitions such as pedestrian detection, traffic sign detection and recognition
  • Route guidance systems
  • Trip modeling and driver speed prediction
  • Vehicle energy management and optimization in hybrid vehicles

Paper Submission

Potential authors are encouraged to submit their manuscripts to the special session through WCCI2016 submission system. All the submissions will go through peer review. Details on manuscript submission can be found from http://www.wcci2016.org/submission.php

Important Dates

Paper submission deadline: January 15, 2016
Notification of acceptance: March 15, 2016
Final paper submission and early registration deadline: April 15, 2016

Organizers

Yi Lu Murphey at University of Michigan-Dearborn, USA
Mahmoud Abou-Nasr at Ford Motor Company, USA
Ishwar K Sethi at Oakland University, USA
Robert Karlsen at US Army TARDEC
Chaomin Luo at University of Detroit Mercy, USA
Ana Bazzan, Federal do Rio Grande do Sul, Brazil


Wednesday, 23 December 2015

Call for Papers The 3rd International Conference on Behavioral, Economic, and Socio-Cultural Computing


URL: http://besc-conf.org/2016
Submission System: https://easychair.org/conferences?conf=besc2016

All accepted conference papers will be published by IEEE and included in the IEEE Xplore Digital Library and EI Compendex. Top quality papers after presented in the conference will be selected for extension and publication in the special issue of international journals.

Important Dates

Paper Submission Due: 01/07/2016
Author Notification Due: 15/08/2016
Camera Ready Due: 01/09/2016
Conference date: 10-13/11/2016

Conference Scope

The 3rd International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC2016) will take place in Hilton Gardon Inn, South Point, Durham, NC, USA, 10-13 November, 2016.
 
BESC aims to become a premier forum in which academic researchers and industry practitioners from data mining, statistics and analytics, business and marketing, finance and politics, and behavioral, economic, social and psychological sciences could present updated research efforts and progresses on foundational and emerging interdisciplinary topics of BESC, exchange new ideas and identify future research directions.

All accepted conference papers will be published by IEEE and included in the IEEE Xplore Digital Library and EI Compendex. Top quality papers after presented in the conference will be selected for extension and publication in the special issue of international journals. The conference committee invites submissions of applied or theoretical research and application-oriented papers on any below areas/tracks.

Topics of Interest

Papers are invited in the areas below, but do not exclude research in the general areas of the topic headings.

(1) Social Computing and Applications
  • Social behavior
  • Social network analysis and mining
  • Semantic web
  • Social intelligence
  • Security, privacy, trust and cryptography in social contexts
  • Social commerce and related applications
  • Social recommendation
  • Data mining
(2) Behavioral and Economic Computing
  • Agent-based modeling
  • Artificial/experimental markets
  • Asset pricing
  • Computational finance
  • Financial crises
  • Monetary policy
  • Optimization
  • Volatility modeling
  • Evolutionary economics
(3) Information Management and Systems
  • Decision Analytics
  • E-Business
  • Societal impacts of IS
  • Human behavior and IS
  • IS in healthcare
  • IS security and privacy
  • IS strategy, structure and organizational impacts
  • Service science and IS
(4) Digital Humanities
  • Digital media
  • Digital humanities
  • Digital games and learning
  • Digital footprints and privacy
  • Twitter histories creation
  • Crowd dynamics
  • Digital arts
  • Mobile technologies
  • Activity streams and experience design
(5) User Modeling, Privacy, and Ethics
  • Personalization for individuals, groups and populations
  • Large scale personalization, adaptation and recommendation
  • Web dynamics and personalization
  • Privacy, perceived security and trust

Paper Submissions

All papers will be reviewed by the Program Committee on the basis of technical quality, relevance to BESC 2016, originality, significance and clarity. Please note:
  • All submissions should use IEEE two-column style. Templates are available from http://www.ieee.org/conferences_events/conferences/publishing/templates.html
  • All papers must be submitted electronically through the paper submission system in PDF format only, BESC2016 accepts scientific papers (6 pages), short papers (2 pages) and demo papers (2 pages).
  • Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings.
  • Papers must be clearly presented in English and will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation.
  • Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work.
Paper submission system is available at: https://easychair.org/conferences/?conf=besc2016

Organizers


General Chair

Paul Wang, Duke University, USA


Conference Chair

Leon S.L. Wang, National University of Kaohsiung, Taiwan

Program Committee Co-chairs

Gang Li, Deakin University, Australia
Yves Demazeau, CNRS, France

Sponsorship Chair

Guandong Xu, University of Technology Sydney, Australia

Track Chairs

Social Computing and Applications:
Gang Li, Deakin University, Australia
Behavioral and Economic Computing:
Herbert Dawid
Information Management and Systems:
Wu HE, Old Dominion University
Digital Humanities:
JianBo Gao
User Modeling, Privacy, and Ethics
Yidong Li, Beijing Jiaotong University,

Industry Chair

Alvin Chin, BMW Group, USA
Xin Li, iFlyTek Research, China

Publication Chair

Guanfeng Liu, Suchoo University

Publicity Chair

Shaowu Liu, Deakin University
Jie Kong, Xi'an Shiyou University

Call for Papers 16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems



The IPMU conference is organized every two years with the focus of bringing together scientists working on methods for the management of uncertainty and aggregation. It also provides a forum for the exchange of ideas between theoreticians and practitioners in these and related areas. 2016 edition of IPMU will take place at Eindhoven University of Technology (TU/e), in Eindhoven, The Netherlands. The Eindhoven region has become one of the leading technology hotspots in Europe, which is also known by the name Brainport Eindhoven. This region is a breeding ground for innovation and the home base for companies, and world-class knowledge and research institutes. Many top international high-tech companies are located in Eindhoven, such as Philips, DAF Trucks and ASML. Eindhoven offers good social and cultural facilities, concerts halls, theatres and museums. Numerous cafés and restaurants lend the town center the pleasant and lively air of a big city.


Topics and Scope of the Conference 

Theory, Methods and Tools: Uncertainty, Bayesian and Probabilistic Methods, Information Theory, Measures of Information and Uncertainty, Evidence and Possibility Theory, Utility Theory, Fuzzy Sets and Fuzzy Logic, Rough Sets, Multiple Criteria Decision Methods, Aggregation Methods, Knowledge Representation, Approximate Reasoning, Non-classical Logics, Default Reasoning, Belief Revision, Argumentation, Ontologies, Uncertainty in Cognition, Graphical Models, Knowledge Acquisition, Machine Learning, Evolutionary Computation, Neural Networks, Data Analysis and Data Science.

Application Fields: Intelligent Systems and Information Processing, Decision Support, Database and Information Systems, Information Retrieval and Fusion, Image Processing, Multi-Media, Agents, Pattern Recognition, Medicine and Bioinformatics, Finance, Software Engineering, Industrial Engineering, Big Data.

Call for papers:
IPMU'2016 solicits original research contributions of theoretical and methodological nature as well as application-oriented work.

Tutorials:
The first day of the conference will host tutorials given by renowned researchers.

IPMU 2016 is technically co-sponsored by IEEE CIS. 

Details for the submission and all information concerning the conference can be found at the conference website: 
www.ipmu2016.org.


IMPORTANT DATES: 
Special session proposals:
October 31st, 2015
Notification of acceptance special sessions:
November 15th, 2015
Paper submission:
January 22nd, 2016
Notification of acceptance:
March 1st, 2016
Camera-ready paper submission:
March 31st, 2016
Early/author registration:
March 31st, 2016
Conference:
June 20-24th, 2016
Tutorials:
June 20th, 2016


Executive Directors:
Bernadette Bouchon-Meunier (France) Ronald R. Yager (USA)
General Chair:
Uzay Kaymak (The Netherlands) 
Program Chairs:
Marie-Jeanne Lesot (France) João Paulo Carvalho (Portugal) 
Finance Chair:
Anna Wilbik (The Netherlands) 
Publicity Chair:
Rui Jorge Almeida (The Netherlands)
Special Session Chair:
João M. C. Sousa (Portugal)
Publication Chair:
Susana Vieira (Portugal)
Sponsor Chair:
Paul W.P.J. Grefen (The Netherlands) 

Monday, 21 December 2015

Call for Papers 2016 IEEE Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)

To increase the quality of life and better support the economical development, we often appreciate adaptable solutions, simple interfaces, and virtual views for enhanced operation. The wide and increasing needs of adaptable and flexible solutions for many industrial, environmental, engineering, educational, entertainment, and biomedical applications point out the importance of using design methodologies and implementation technologies with high ability of adaptation and evolution. Computational intelligence is one of the most relevant answers to such needs. Virtual environments and human-computer interfaces are essential to effectively understand the operating environment and support interactive applications.

Papers are solicited on all aspects of computational intelligence, human-computer interaction technologies, and virtual environments for measurement systems and the related applications, from the points of view of both theory and practice. This includes, but is not limited to, the following topics with specific emphasis on the computational intelligence and measurement aspects:
  • Intelligent measurement systems
  • Human-computer interaction
  • Augmented and virtual reality
  • Accuracy and precision of neural/fuzzy components and virtual environments
  • Perception, neurodynamics, neurophysiology, psychophysics
  • Multimodal sensing
  • Multimodal virtual environments
  • Sensors and displays
  • Calibration
  • Multi-sensor data fusion
  • Computational intelligence technologies for identification, prediction, control, system diagnosis, quality measurement, and optimization
  • Intelligent monitoring and control systems
  • Neural and fuzzy signal/image processing for industrial, environmental and domotic applications
  • Standards
  • Fuzzy and neural components for embedded systems
  • Image understanging and recognition
  • Reliability of fuzzy and neural components
  • Object and system model validation
  • Virtual reality languages
  • Computational intelligence for robotics and vision
  • Computational intelligence for medical and bioengineering applications
  • Computational intelligence for entertainment and educational applications
  • Collaborative distributed virtual environments
  • Model-based telecommunications and telecontrol
  • Hardware implementation of neural and fuzzy systems for measurements
  • Neural and fuzzy techniques for entertainment and educational applications

Details for the submission and all information concerning the conference can be found at the conference website: http://2016.civemsa.ieee-ims.org. Submit full papers by February 1, 2016.

Honorary Co-Chairs

Imre Rudas, Obuda University, Hungary
Hairong Zheng, SIAT, China

General Co-Chairs

Annamaria R. Varkonyi-Koczy, Obuda University, Hungary
Stefano Ferrari, Università degli Studi di Milano, Italy
Yong Hu, The University of Hong Kong, IBME CAMS, China

Program Co-Chairs

Ruggero Donida Labati, Università degli Studi di Milano, Italy
Shervin Shirmohammadi, University of Ottawa, Canada
Tamas Szakacs, Obuda University, Hungary

Wednesday, 16 December 2015

IJCNN 2016 Plenary Speakers

IEEE WCCI 2016 is pleased to announce the following IJCNN Plenaries:

  1. Jürgen Schmidhuber, 2016 IEEE CIS Neural Networks Pioneer Awardee
  2. Bin He, IEEE Fellow, Editor-in-Chief of IEEE Transactions on Biomedical Engineering
  3. Marios M. Polycarpou, IEEE Fellow, 2016 IEEE CIS Neural Networks Pioneer Awardee
  4. Jun Wang, IEEE Fellow, 2014 IEEE CIS Neural Networks Pioneer Awardee
  5. Haibo He, Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems (Beginning in 2016)
More Plenaries will be announced soon. Visit http://wcci2016.org/speakers.php?id=ijcnn for more information.

Call for Papers WCCI 2016 Special Session "Advances in Decomposition-based Evolutionary Multi­objective Optimization (ADEMO)"

1st Special Session on Evolutionary Multi-objective Optimization based on Decomposition
https://sites.google.com/site/bilelderbelpro/home/ademo-cec16

Aims and Scope

The purpose of this special session is to promote the design, study, and validation of generic approaches for solving multi­-objective optimization problems based on the concept of decomposition. Decomposition-based Evolutionary Multi-­objective Optimization (DEMO) encompasses any technique, concept or framework that takes inspiration from the "divide and conquer" paradigm, by essentially breaking a multi-­objective optimization problem into several sub­problems for which solutions for the original global problem are computed and aggregated in a cooperative manner.

We encourage contributions reporting advances with respect to other decomposition techniques operating in the decision space or other hybrid approaches taking inspiration from operations research and mathematical programming. Many different DMOEAs variants have been proposed, studied and applied to various application domains. However, DEMOs are still in their very early infancy, since only few basic design principles have been established compared to the huge body of literature dedicated to other well-established approaches (e.g. Pareto ranking, indicator-based techniques, etc). The main goal of the proposed session is to encourage research studies that systematically investigate the critical issues in DMOEAs at the aim of understanding their key ingredients and their main dynamics, as well a to develop solid and generic principles for designing them. The long term goal is to contribute to the emergence of a general and unified methodology for the design, the tuning and the performance assessment of DEMOs.

Topics of interests

The topics of interests include (but are not limited to) the following issues:
  1. Analysis of algorithmic components and performance assessment of DEMO approaches. Experimental and theoretical investigations on the accuracy of the underlying decomposition strategies, e.g. scalarizing functions techniques, multiple reference points, variable grouping, etc. 
  2. Adaptive, self­adaptive, and tuning aspects for the parameter setting and configuration of DEMO approaches. 
  3. Design and analysis of new DEMO approaches dedicated to specific combinatorial, constrained and/or continuous domains. 
  4. Effective hybridization of single-objective solvers with DEMO approaches, i.e., plug and­ play algorithms based on traditional single objective evolutionary algorithms and meta­ heuristics, such as: Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Covariance Matrix Evolution Strategy (CMA­ES), Scatter Search (SS), etc. 
  5. Adaptation and analysis of DEMO approaches in the context of large scale and many objective problem solving 
  6. Application of DEMO for solving real-­world problems. 
  7. Design and implementation of DEMO approaches in massively parallel and large scale distributed environment (e.g., GPUs, Clusters, Grids, etc). 
  8. Software tools for the design implementation and performance assessment of DEMO approaches

Deadlines and Submission

Submission Deadline: Jan 15, 2016
Notification Due: Mar 15, 2016
Final Version Due: Apr 15, 2016

For the 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 2016 paper submission site: http://ieee-cis.org/conferences/cec2016/upload.php 
  3. Select "7bn. Advances in Decomposition-­based Evolutionary Multi­objective Optimization (ADEMO)" 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.

Links information

http://www.wcci2016.org/
https://sites.google.com/site/bilelderbelpro/home/ademo-cec16
http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=49846&copyownerid=83312

Organizers and Contact

Saúl Zapotecas­-Martínez (saul.zapotecas@gmail.com)
SHINSHU University, Japan
DOLPHIN, Inria Lille Nord Europe, France

Bilel Derbel (bilel.derbel@univ­lille1.fr)
University Lille 1, CRIStAL CNRS UMR9189, France
DOLPHIN, Inria Lille Nord Europe, France

Qingfu Zhang (qingfu.zhang@cityu.edu.hk)
City University of Hong Kong, Hong Kong

Carlos A. Coello Coello (ccoello@cs.cinvestav.mx)
CINVESTAV­IPN, Mexico

Sunday, 13 December 2015

Call for Papers WCCI 2016 Special Session "Information Fusion and Fuzzy Linguistic Decision Making"

Organizers:

Luis Martínez, Rosa M Rodríguez and Francisco Herrera

Brief Description:

Decision Making is an inherent mankind task related to intelligent and complex activities in which human beings face situations where they must choose among different alternatives by means of reasoning and mental processes. Such decision situations usually involve different types of uncertainty according to their nature. The fusion of information can reduce uncertainty and facilitate the decision making process because it associates, correlates and combines information from multiple sources to provide a relevant and timely view of the situation.

Therefore, information fusion in decision making has been widely studied from different points of view according to the framework in which it should be developed. However, there are still different open challenging problems related to information fusion and decision making because of the necessity of dealing with either novel decision making problems with new types of uncertainty and their modelling or with the advances in information fusion that imply improvements regarding previous approaches.

Additionally, many real decision situations are defined under uncertain contexts with imprecise information, in which it is straightforward the use of linguistic information. Fuzzy linguistic approach based models and Computing with Words (CW) provides the tools and methodology to deal with words. CW emulates human cognitive processes to improve decision solving processes under uncertainty. Consequently, information fusion processes, fuzzy linguistic approach and CW have been applied as modelling and computational basis for linguistic decision making, because it provides tools close to human beings reasoning processes related to decision making, which improve and facilitate the resolution of decision making under uncertainty as linguistic decision making.

All Information Fusion, Decision Making, Fuzzy Linguistic Approach and Computing with Words have recently attracted much attention in which, novel mathematical foundations and new decision models raised to be applied in different decision fields such as multi-criteria decision making, decision analysis, evaluation processes, consensus reaching processes, etc.

Objectives and topics:

This invited session aims at providing an opportunity for researchers working in both research areas to discuss and to share their new ideas, original research results and practical experiences. More specifically, we expect you to have any contribution with the focus on the use of linguistic modelling in decision making. The topics of this special session are as follows:
  • Fusion Methods for Linguistic Decision making
  • Linguistic expression domains to represent preferences
  • Linguistic hesitant for modeling preference
  • Multi-criteria and group decision making
  • Selection and consensus models with linguistic information
  • Combining Heterogeneous Information in Decision Making
  • Multi-Level Fusion for Decision Making
  • Large Scale Decision Making
  • Fusing Linguistic Information in Decision Making
  • Intelligent Decision Support Systems
  • Dynamic Decision Making
  • Context-Based Information Fusion
  • Fusion in Networked Systems
  • Linguistic decision making in Engineering evaluation, resource management and transfer, Industry applications, sensory evaluation, evaluation and recommendation, Investments applications and risk assessment, …

Important Dates:

Submission Deadline: 15th January 2016
Notification Acceptance: 15th March 2016
Final paper submission deadline: 15th April 2016

Paper Submission

Procedure for paper formatting should be followed as specified on the WCCI’2016 website (http://www.wcci2016.org/).

Submitted papers for this Special Session should be uploaded from the website provided for uploading (http://ieee-cis.org/conferences/fuzzieee2016/upload.php) and choose in Main Research Topic the choice SS33 Information Fusion and Fuzzy Linguistic Decision Making.

Contact information:

Luis Martínez
Email address: luis.martinez@ujaen.es

Rosa M. Rodríguez
Email address: rosam.rodriguez@decsai.ugr.es

Francisco Herrera
Email address: herrera@decsai.ugr.es

Thursday, 10 December 2015

WCCI 2016 Public Lecture and Panel Session

IEEE WCCI 2016 is pleased to announce a Public Lecture on "Fun and Games with Artificial Intelligence" by David B. Fogel. Visit http://wcci2016.org/speakers.php for more information.

IEEE WCCI 2016 is pleased to announce a Panel Session on “IEEE and CIS in the Next Decade”. Members of the panel session include
1. Barry L. Shoop (2016 IEEE President),
2. Vincenzo Piuri (2015 IEEE VP - Technical Activities),
3. Jacek M. Zurada (2014 IEEE VP - Technical Activities),
4. Xin Yao (2014-2015 IEEE CIS President),
5. Marios M. Polycarpou (2012-2013 IEEE CIS President) and
6. Pablo A. Estévez (Moderator, 2016-2017 IEEE CIS President).

Visit http://goo.gl/iNt84J for more information.

Call for Papers WCCI / IJCNN 2016 Special Session "DISTRIBUTED LEARNING ALGORITHMS FOR NEURAL NETWORKS"

http://ispac.diet.uniroma1.it/ijcnn-2016-special-session-distributed-nn

Scope and motivations

In the era of big data and pervasive computing, it is common that datasets are distributed over multiple and geographically distinct sources of information (e.g. distributed databases). In this respect, a major challenge is designing adaptive training algorithms in a distributed fashion, with only partial or no reliance on a centralized authority. Indeed, distributed learning is an important step to handle inference within several research areas, including sensor networks, parallel and commodity computing, distributed optimization, and many others.

Based on the idea that all the aforementioned research fields share many fundamental questions and mechanisms, this special session is intended to bring forth advances on distributed training for neural networks. We are interested in papers proposing novel algorithms and protocols for distributed training under multiple constraints, analyses of their theoretical aspects, and applications for multiple source data clustering, regression and classification.

Topics

The topics of interest to be covered by this Special Session include, but are not limited to:
  • Distributed algorithms for training neural networks and kernel methods
  • Theoretical aspects of distributed learning (e.g. fundamental communication constraints)
  • Learning on commodity computing architectures and parallel execution frameworks (e.g. MapReduce, Storm)
  • Energy efficient distributed learning
  • Distributed semi-supervised and active learning
  • Novel results on distributed optimization for machine learning
  • Cooperative and competitive multi-agent learning
  • Learning in realistic wireless sensor networks
  • Distributed systems with privacy concerns (e.g. healthcare systems)
   

Important dates

  • Paper submission deadline: January 15, 2016
  • Notification of paper acceptance: March 15, 2016
  • Camera-ready deadline: April 15, 2016
  • Conference: July 25-29, 2016
   

Further details

For additional details, please visit the special session's website, or contact one of the organizers:
  • Massimo Panella, Sapienza University of Rome (massimo [dot] panella [at] uniroma1 [dot] it).
  • Simone Scardapane, Sapienza University of Rome (simone [dot] scardapane [at] uniroma1 [dot] it).
   

Call for Papers WCCI / CEC 2016 Special Session "Automated Design: Hyper-Heuristics and Metaheuristics (ADHM 2016)"

http://titancs.ukzn.ac.za/CEC2016SpecialSession.aspx

Aims, Scope and List of Topics

Designing metaheuristics to solve problems can be time consuming, requiring many man hours. This involves making a number of design decisions such as parameter tuning, identifying moves or operators to use, deciding on the control flow of the algorithm or determining which low-level heuristics to use in the case of combinatorial optimization problems. In some cases it may be necessary to create new operators or algorithms or hybridize different metaheuristics to solve a problem. Hyper-heuristics and adaptive metaheuristics have proven to be effective for making some of these design decisions, thereby facilitating automated design. Hyper-heuristics have been successfully used for the selection and generation of lowlevel heuristics in solving various combinatorial optimization problems including timetabling, vehicle routing and packing problems, amongst others and have also been applied to dynamic environments and multiobjective optimization. More recent trends in hyper-heuristic research have focused on the design of metaheuristics. Selection hyper-heuristics have been used for determining parameter values, choice of operators and control flow in metaheuristics, e.g. evolutionary algorithms and ant colonization, as well as for the hybridization of techniques, e.g. multiobjective evolutionary algorithms, different metaheuristics.

Generation hyper-heuristics have been employed to create new operators for metaheuristics, e.g. selection and mutation operators. An emerging area in hyper-heuristics is hyper-hyper-heuristics, i.e. using hyper-heuristics to generate or design hyper-heuristics. The aim of this special session is for researchers to present recent developments in the field thereby paving the way for future advancement.

The main topics include but are not limited to:
  • Applications of selection and generative hyper-heuristics
  • Hyper-heuristics for metaheuristic design, e.g. parameter tuning, control flow, operator selection
  • Hyper-heuristics for the creation of new operators and algorithms
  • Hyper-heuristics for the derivation of hybrid methods, e.g. hybridization of metaheuristics
  • Hyper-heuristics for the design hyper-heuristics
  • Cross domain applications of hyper-heuristics
  • Parallelization of hyper-heuristics
  • Theoretical aspects of hyper-heuristics

Organizers

Nelishia Pillay,
University of KwaZulu-Natal, South Africa
E-mail: pillayn32@ukzn.ac.za

Rong Qu,
University of Nottingham, UK
E-mail: Rong.Qu@nottingham.ac.uk

Hisao Ishibuchi,
Osaka Prefecture University, Japan
E-mail: hisaoi@cs.osakafu-u.ac.jp

Important Dates

Paper submission deadline: 15 January, 2016
Paper acceptance notification: 15 March, 2016
Final paper submission deadline: 15 April, 2016
Early registration: 15 April, 2016

Paper Submission

Special session papers are treated the same as regular papers and must be submitted via the CEC 2016 submission website. When submitting choose the "Automated Design: Hyper-Heuristics and Metaheuristics" special session from the "Main Research Topic" list.

Tuesday, 8 December 2015

Call for Papers WCCI / CEC 2016 Special Session "Quantum Computing and Evolutionary Computation"

As quantum information and computation research continues to develop, we will see increasing interest in adapting the philosophy of quantum computing, information theory and ideology into other, more traditional aspects of computational research. Although the hardware technology to realize quantum computing is still yet to be materialized, research about the theoretical aspects of quantum computing and its ideology has enjoyed some success with artificial and computational intelligence.

The main aim of this special session is to bring together experts in algorithms, quantum information, quantum algorithms, physicists and hardware designers to discover new applications and features resulting from not only a cross-disciplinary information exchange but also from discussion between engineers and scientists working in the larger area of quantum information and computation.

Scope and main Topics

This special session focus on combining various aspects of quantum computing, information theory, and other aspects with existing fields in computational intelligence. In particular the usage of classical algorithms to solve quantum problems, usage of quantum algorithms to solve classical problems and the usage of quantum algorithms for solving quantum problems are three main sought general ideas to be the center focus of this special session.

Research areas that will be discussed in this special session include (but are not limited
to) the following:
  • Quantum inspired evolutionary computation, quantum inspired genetic algorithms.
  • Quantum evolutionary computing related areas such as quantum neural networks and quantum fuzzy computing systems.
  • Evolutionary Techniques and Quantum Computing. Including: (a) use of evolutionary paradigms to create quantum circuits, quantum algorithms, quantumarchitectures and quantum games, (b) creation of new quantum algorithms and architectures inspired by the concepts of evolution and other biological ideas,(c) use of evolutionary algorithms to solve any practical problems in designing quantum devices.
  • Quantum implementation of Computational Intelligence: many machine learning and problem solving models known from Computational Intelligence such as Neural Nets, Bayesian networks, Logic Networks, Fuzzy Logic, state machines, evolvable hardware, etc., can be extended to those based on quantum circuits and automata.
  • Computational Intelligence interacting with various aspects of Quantum information theory including error correction, teleportation, encryption/decryption, security, etc.
  • Quantum game theory, applications of quantum games.
  • Using GA, GP and other evolutionary and biological paradigms in all areas of quantum circuits, quantum information and quantum computing.
  • Applications of quantum concepts in Computational Intelligence, Multimedia and Robotics.
  • Quantum entanglement, and applications in communication, computing, information theory, etc.
  • Quantum probability and its applications.

Important Dates

Paper submission deadline: 15th January 2016
Paper acceptance notification date: 16th March 2016
Camera ready paper submission deadline: 15th April 2016
For submission details please visit: http://ieee-cis.org/conferences/cec2016/upload.php.
In the Main Research Topic specify 7bu. Quantum Computing and Evolutionary Computation.

Organizers

Martin Lukac, William Hung, Claudio Moraga
For details contact Martin Lukac at: martin.lukac@nu.edu.kz

Call for Papers WCCI / CEC 2016 Special Session "Evolutionary Robotics"

General Chairs

Patricia A. Vargas (Heriot-Watt University - United Kingdom)
Joshua Auerbach (EPFL - Lausanne, Switzerland)
Micael Couceiro (Ingenarius, Ltd - Portugal)
Dario Floreano (EPFL - Lausanne, Switzerland)
Phil Husbands (University of Sussex - United Kingdom)

Website: http://lis2.epfl.ch/events/specialsessions/CEC16/

Evolutionary Robotics (ER) aims to apply evolutionary computation techniques, inspired by Darwin’s principle of selective reproduction of the fittest, to automatically design the control and/or hardware of both real and simulated autonomous robots.

Having an intrinsic interdisciplinary character, ER is being employed towards the development of many fields of research, among which we can highlight neuroscience, cognitive science, evolutionary biology and robotics.

Hence the objective of this special session is to assemble a set of high-quality original contributions that reflect and advance the state-of-the-art in the area of Evolutionary Robotics, with an emphasis on the cross-fertilisation between ER and the aforementioned research areas, ranging from theoretical analysis to real-life applications.

Papers Publication

Papers accepted to this special session track will be published in the IEEE CEC proceedings.

Post Conference Publication

Authors of best papers will be asked to contribute to a journal special issue on the topic of "Evolutionary Robotics".

Paper Submission

Submissions should follow the guidance given on the IEEE CEC 2016 conference website: http://www.wcci2016.org/submission.php

When submitting, please select in the submission system the respective special session title under the list of Main research topic: Evolutionary Robotics.

All submissions will be peer-reviewed with the same criteria used for other contributed papers. All accepted papers will be included and published in the conference proceedings.

Topics of interest include (but are not restricted to):

  • Evolution of robots which display minimal cognitive behaviour, learning, memory, spatial cognition, adaptation or homeostasis.
  • Evolution of neural controllers for robots, aimed at giving an insight to neuroscientists, evolutionary biologists or advancing control structures.
  • Evolution of communication, cooperation and competition, using robots as a research platform.
  • Co-evolution and the evolution of collective behaviour.
  • Evolution of morphology in close interaction with the environment, giving rise to self-reconfigurable, self-designing, self-healing, self-reproducing, humanoid and walking robots.
  • Evolution of robot systems aimed at real-world applications as in aerial robotics, space exploration, industry, search and rescue, robot companions, entertainment and games.
  • Evolution of controllers on board real robots or the real-time evolution of robot hardware.
  • Novel or improved algorithms for the evolution of robot systems.
  • The use of evolution for the artistic exploration of robot design.

Important Dates

Paper Submission: January 15, 2016
Notification of Acceptance: March 15, 2016
Camera-Ready Submission: April 15, 2016

Call for Papers WCCI 2016 Special Session "Evolutionary Computation for Human Center Decision Making Systems: Trends and Applications"

It is our great pleasure to invite you to submit a paper for the Special Session: Evolutionary Computation for Human Center Decision Making Systems: Trends and Applications.

Decision Support Systems are interactive software-based system intended to support business and organizational decision-making activities in order to help decision makers to compile information, model business processes, solve problems and make decisions. This special session should address the design of decision support systems with dynamic adaptation and optimization become increasingly important incorporating expert’s knowledge from an Ambient Intelligence perspective. It gives relevance to the idea of human-centered design and the intelligence needed to allow systems to foresee user’s needs and preferences.

This special session intends to present and discuss the integration of recent developments of Evolutionary Computation, Self-Organization, Decision Support Systems, Information System and Human Computer Interaction and Ambient Intelligence, in general.

Scope and Topics

The topics of interest for this special session include, but are not limited to:
  • Evolutionary Computation Optimization-based decision support models
  • Collaborative support systems
  • Human-Computer Interaction for Interactive Systems
  • Web-based Decision Support Systems
  • Intelligent User Interfaces
  • User Modeling preferences
  • Natural interfaces and ambiguity solving techniques
  • Intelligent Agents and Multi-Agent Systems
  • Hybrid Intelligent Systems
  • Self-Organized, Autonomic Computing and Distributed Systems
  • Intelligent Manufacturing Systems
  • Applications: Manufacturing, Logistics and Supply chain management, Biomedical and Bioinformatics, Business, Medicine, Banking, Financing, Social Networks, Workflow

Paper Submission

Potential authors may submit their manuscripts for presentation consideration through WCCI2016 submission system, selecting the special session. All the submissions will go through peer review. Details on manuscript submission can be found from http://ieee-cis.org/conferences/cec2016/upload.php

Important Dates

Paper submission deadline: January 15, 2016
Notification of acceptance: March 15, 2016
Final paper submission and early registration deadline: April 15, 2016

Organizers

Ana Maria Madureira (amd@ieee-pt.org)
Ivo Pereira (iaspe@isep.ipp.pt)
Bruno Cunha (BMACA@isep.ipp.pt)

Monday, 7 December 2015

Call for Papers WCCI / IJCNN 2016 Special Session "Deep Learning, Medical Imaging, and Translational Medicine"

Introduction

Deep learning has demonstrated its capability for many vision problems, such as face detection and recognition, image classification, etc. It is expected that this technique can benefit the area of medical image analysis, as well as imaging-based translational medicine. Though a few pioneering works can be found in the literature, there are still a lot of unresolved issues when applying deep learning for medical images.

Scope and Topics

Topics include, but are not limited to:
  • Image descriptor and feature extraction
  • Image super-resolution
  • Image reconstruction
  • Image registration
  • Image segmentation and labeling
  • Computer-assisted lesion detection
  • Computer-assisted diagnosis
  • Deep learning model selection
  • Meta-heuristic techniques for fine-tuning parameter in deep learning-based archi-tectures
  • Other related translational medical applications.

Paper Submission

  • Only papers prepared in PDF format will be ac-cepted.
  • Paper Length: Up to 8 pages, including figures, tables and references. At maximum, two add-tional pages are permitted with over-length page charge of US$100/page, to be paid during author registration.
  • Paper Formatting: double column, single spaced, #10 point Times Roman font.
  • Margins: Left, Right, and Bottom: 0.75" (19mm). The top margin must be 0.75" (19 mm), except for the title page where it must be 1" (25 mm).

Key Dates

  • Paper Submission DDL 15 Jan 2016
  • Paper Acceptance Notification 15 Mar 2016
  • Final Paper Submission DDL 15 Apr 2016
  • IEEE WCCI 2016 25-29 Jul 2016

 

Organization

  • Qian Wang, Shanghai Jiao Tong Univ.
  • Jun Shi, Shanghai Univ.
  • Shihui Ying, Shanghai Univ.
  • Manhua Liu , Shanghai Jiao Tong Univ.
  • Yonghong Shi, Fudan Univ.

Call for Papers WCCI / IJCNN 2016 Special Session "Computational Intelligence for Unmanned Systems"

Overview

An unmanned system(US) is a machine or device that is equipped with necessary data processing units, sensors, automatic control, and communications systems and is capable of performing missions autonomously without human intervention. Unmanned systems include unmanned aircraft, ground robots, underwater explorers, satellites, and other unconventional structures. Computational Intelligence(CI) includes classical evolutionary computation, neural computation, fuzzy systems, swarm intelligence(Particle Swarm Optimization, Ant Colony Optimization,.etc.) and other new CI methods such as Bee colony optimization algorithms, Biogeography Based Optimization, Firefly algorithms or hybridizations of CI approaches.

Topics of Interest

This special session aims to cover all subjects of Unmanned Systems relating to the development of automatic machine systems based on CI, which include advanced technologies in unmanned hardware platforms (aerial, ground,underwater and unconventional platforms), unmanned software systems, energy systems, modeling and control, communications systems, computer vision systems, sensing and information processing, navigation and path planning and innovative application case studies.

Authors are invited to submit their original and unpublished work to this special session. Topics of interest include but are not limited to: CI methods solving technical issues underlying the development of unmanned systems.

  • Biologically-inspired computing for US
  • CI for motion planning of unmanned aircraft, ground robots, underwater explorers 
  • CI for navigation, mapping and localization of unmanned aircraft, ground robots, underwater explorers 
  • CI for image processing of unmanned aircraft, ground robots, underwater explorers
  • Bio-inspired system on US 
  • Artificial Neural Networks for US 
  • CI on machine learning, intelligent systems design for unmanned hardware platforms (aerial, ground, underwater and unconventional platforms) 
  • CI on machine learning and intelligent systems design for unmanned software systems 
  • CI for energy systems of US 
  • CI for modeling, control and communication systems of US 
  • CI for computer vision systems of US 
  • CI for sensing and information processing of US 
  • Theory and applications of CI and machine learning systems for US 
  • Swarm intelligence for unmanned aircraft, ground robots, underwater explorers and other unconventional structures

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 Computational Intelligence for Unmanned Systems.

Important Dates

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

Organisers

Hongwei Mo, Harbin Engineering University, China, honwei2004@126.com
Chaomin Luo, University of Detroit Mercy, Michigan, USA.

Call for Papers WCCI / IJCNN 2016 Special Session "DEEP REINFORCEMENT LEARNING"

ORGANIZED BY

ABDULRAHMAN ALTAHHAN  VASILE PALADE, JUNYU DONG, XINGHUI DONG, HUI YU AND MOHAMED CHERIET
SCHOOL OF COMPUTING, ELECTRONICS AND MATHS, FACULTY OF ENGINEERING, COVENTRY UNIVERSITY

Deep Learning has been under the focus of neural network research and industrial communities due to its proven ability to scale well into difficult problems and due to its performance breakthroughs over other architectural and learning techniques in important benchmarking problems. This was mainly in the form of improved data representation in supervised learning tasks. Reinforcement learning (RL) is considered the model of choice for problems that involve learning from interaction, where the target is to optimize a long term control strategy or to learn to formulate an optimal policy. Typically these applications involve processing a stream of data coming from different sources, ranging from central massive databases to pervasive smart sensors.

RL does not lend itself naturally to deep learning and currently there is no uniformed approach to combine deep learning with reinforcement learning despite good attempts. Examples of important open questions are: How to make the state-action learning process deep? How to make the architecture of an RL system appropriate to deep learning without compromising the interactivity of the system? Etc. Although recently there have been important advances in dealing with these issues, they are still scattered and with no overarching framework that promote them in a well-defined and natural way.

This special session will provide a unique platform for researchers from Deep Learning and Reinforcement Learning communities to share their research experience towards a uniformed Deep Reinforcement Learning (DRL) framework in order to allow this important interdisciplinary branch to take-off on solid grounds. It will focus on the potential benefits of the different approaches to combine RL and DL. The aim is to bring more focus onto the potential of infusing reinforcement learning framework with deep learning capabilities that could allow it to deal more effectively with present applications including, but not restricted to, online streamed data processing that involves actions.

SCOPE AND TOPICS

  1. Novel DRL Algorithms
  2. Novel DRL Neural Architectures
  3. Adaptation of existing RL Techniques for Deep Learning
  4. Optimization and convergence proofs for DRL algorithms
  5. Deeply Hierarchical RL
  6. DRL architecture and algorithms for Control
  7. DRL architecture and algorithms for Robotics
  8. DRL architecture and algorithms for Time Series
  9. DRL architecture and algorithms for Big Streamed Data Processing
  10. DRL architecture and algorithms for Optimizing Governmental Policy
  11. Other DRL applications

Call for Papers WCCI / IJCNN 2016 Special Session "Deep Learning for Big Multimedia Understanding"

Conventional multimedia understanding is usually built on top of handcrafted features, which are often much restrictive in capturing complex multimedia content. Recent progress on deep learning opens an exciting new era, placing multimedia understanding on a more rigorous foundation with automatically learned representations to model the multimodal data and the cross-media interactions. Existing studies have revealed promising results that have greatly advanced the state-of-the-art performance in a series of multimedia research areas, from the multimedia content analysis, to modeling the interactions between multimodal data, to multimedia content recommendation systems, to name a few here.

Scope and Topics

This special session aims to provide a forum for the presentation of recent advancements in deep learning research that directly concerns the multimedia community. For multimedia research, it is especially important to develop deep learning methods to capture the dependencies between different genres of data, building joint deep representation for diverse modalities. The list of topics includes and is not restricted to the following:
  1. Novel deep network architectures for multimodal data representation
  2. Deep learning for new multimedia applications
  3. Efficient training and inference methods for multimedia deep networks
  4. Emerging applications of deep learning in multimedia search, retrieval and management
  5. Deep learning for multimedia content analysis and recommendation
  6. Deep learning for cross-media analysis, knowledge transfer and information sharing
  7. Distributed computing, GPUs and new hardware for deep learning in multimedia research
  8. Other deep learning topics for multimedia computing, involving at least two modalities

Submission

  • Paper submission deadline is on January 15, 2016.
  • All papers must be submitted through the IEEE WCCI 2016 online submission system. For special session papers, please select the respective special session title “Deep Learning for Big Multimedia Understanding” under the list of research topics in the submission system.

Organizers

Prof. Jinhui Tang, Nanjing University of Science and Technology, China
Dr. Zechao Li, Nanjing University of Science and Technology, China

Sunday, 6 December 2015

Call for Papers WCCI / CEC 2016 Special Session "Brain Storm Optimization Algorithms"

Overview

Swarm intelligence algorithm should have two kinds of ability: capability learning and capacity developing. The capacity developing focuses on moving the algorithm’s search to the area(s) where higher search potential may be obtained, while the capability learning focuses on its actually search from the current solution for single point based optimization algorithms and from the current population for population-based swarm intelligence algorithms.  The swarm intelligence algorithms with both capability learning and capacity developing can be called as developmental swarm intelligence algorithms.

The capacity developing is a top-level learning or macro-level learning methodology. The capacity developing describes the learning ability of an algorithm to adaptively change its parameters, structures, and/or its learning potential according to the search states of the problem to be solved. In other words, the capacity developing is the search strength possessed by an algorithm. The capability learning is a bottom-level learning or micro-level learning. The capability learning describes the ability for an algorithm to find better solution(s) from current solution(s) with the learning capacity it possesses.

The Brain Storm Optimization (BSO) algorithm is a new kind of swarm intelligence, which is based on the collective behaviour of human being, that is, the brainstorming process. It is natural to expect that an optimization algorithm based on human collective behaviour could be a better optimization algorithm than existing swarm intelligence algorithms which are based on collective behaviour of simple insects, because human beings are social animals and are the most intelligent animals in the world. The designed optimization algorithm will naturally have the capability of both convergence and divergence.

The BSO algorithm is a good example of developmental swarm intelligence algorithm. A “good enough” optimum could be obtained through solution divergence and convergence in the search space. In the BSO algorithm, the solutions are clustered into several categories, and the new solutions are generated by the mutation of cluster or existing solutions. The capacity developing, i.e., the adaptation during the search, is another common feature of the BSO algorithms. 

The BSO algorithm can be seen as a combination of swarm intelligence and data mining techniques. Every individual in the brain storm optimization algorithm is not a solution to the problem to be optimized, but also a data point to reveal the landscapes of the problem. The swarm intelligence and data mining techniques can be combined to produce benefits above and beyond what either method could achieve alone.

Topics of Interest

This special session aims at presenting the latest developments of BSO algorithm, as well as exchanging new ideas and discussing the future directions of developmental swarm intelligence. Original contributions that provide novel theories, frameworks, and applications to algorithms are very welcome for this Special Session. Potential topics include, but are not limited to:
  • Analysis and control of BSO parameters
  • Parallelized and distributed realizations of BSO algorithms
  • BSO for Multi-objective optimization
  • BSO for Constrained optimization
  • BSO for Discrete optimization
  • BSO algorithm with data mining techniques
  • BSO in uncertain environments
  • Theoretical aspects of BSO algorithm
  • BSO for Real-world applications

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 Brain Storm Optimization Algorithms.

Important Dates

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

Organisers

Shi Cheng, University of Nottingham Ningbo, China, shi.cheng@nottingham.edu.cn
Quande Qin, Shenzhen University, Shenzhen China, qdqin@szu.edu.cn
Yuhui Shi, Xi'an Jiaotong-Liverpool University, Suzhou China, yuhui.shi@xjtlu.edu.cn
Simone Ludwig, North Dakota State University, USA, simone.ludwig@ndsu.edu

Committee Member

Shangce Gao, University of Toyama, Gofuku, Japan, gaosc@eng.u-toyama.ac.jp
Xingquan Zuo, Beijing University of Posts and Telecommunications, Beijing, China, zuoxq@bupt.edu.cn

Biography of the Proposers

Shi Cheng received the Bachelor's degree in Mechanical and Electrical Engineering from Xiamen University, Xiamen, the Master's degree in Software Engineering from Beihang University (BUAA), Beijing, China, the Ph.D. degree in Electrical Engineering and Electronics from Liverpool University, Liverpool, United Kingdom, the Ph.D. degree in Electrical and Electronic Engineering from Xi’an Jiaotong-Liverpool University, Suzhou, China in 2005, 2008, and 2013, respectively. He is currently a research fellow with Division of Computer Science, University of Nottingham Ningbo, China. He has published more than 30 research articles in peer-reviewed journals and international conferences. His current research interests include swarm intelligence, multiobjective optimization, and data mining techniques and their applications.

Quande Qin received PhD degree in Management Science and Engineering from School of Business Administration, South China University of Technology, Guangzhou, China. Currently, he is a lecturer in the College of Management, Shenzhen University, Shenzhen, China. His current research interests include swarm intelligence, evolutionary optimization and their applications in management and economics.

Yuhui Shi received the PhD degree in electronic engineering from Southeast University, Nanjing, China, in 1992. He is a Professor in the Department of Electrical and Electronic Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, China. Before joining Xi'an Jiaotong-Liverpool University, he was with Electronic Data Systems Corporation, Indianapolis, IN. His main research interests include the areas of computational intelligence techniques (including swarm intelligence) and their applications. Dr. Shi is the Editor-in-Chief of the International Journal of Swarm Intelligence Research.

Simone Ludwig received the PhD degree from Brunel University, UK, in 2004. She is currently an associate professor at North Dakota State University, USA, conducting research in the area of computational intelligence. In particular, developing novel algorithms to address different optimization problems in the area of data mining (large data) and distributed computing. She has published around 90 peer-reviewed articles both in journals and conference proceedings. Dr. Ludwig has served as a co-chair, track chair, and tutorial chair for different conferences, as well as served on numerous conference program committees. In addition, she currently serves on the editorial board of 3 journals.

Shangce Gao received the B.S. degree from Southeast University, Nanjing, China in 2005, and the M.S. and Ph. D. degrees in intellectual information systems and innovative life science from University of Toyama, Toyama, Japan in 2008 and 2011, respectively. He is currently an Associate Professor with the Faculty of Engineering, University of Toyama, Toyama, Japan. From 2011 to 2012, he was an associate research fellow with the Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, China. From 2012 to 2014, he was an associate professor with the College of Information Sciences and Technology, Donghua University, Shanghai, China. His main research interests include computational intelligence, nature-inspired technologies, swarm intelligence, and neural networks for optimization and real-world applications. He was a recipient of the Shanghai Rising-Star Scientist award, the Chen-Guang Scholar of Shanghai award, the Outstanding Academic Performance Award of IEICE, the Outstanding Self-financed Students Abroad Award of Chinese Government, and the Outstanding Academic Achievement Award of IPSJ.

Xingquan Zuo received the Ph.D. degree in Control Theory and Control Engineering from Harbin Institute of Technology, Harbin, China, in 2004. He is currently an Associate Professor in Computer School, Beijing University of Posts and Telecommunications, Beijing, China. From 2012 to 2013, he was a Visiting Scholar in Industrial and System Engineering Department, Auburn University, AL, USA. His research interests are in intelligent optimization and scheduling, evolutionary computation, data mining with applications. He has published more than 70 research papers in journals and conferences, two books and several book chapters. He is a senior member of IEEE and served in program committee of many conferences. 

Call for Papers WCCI / CEC 2016 Special Session "Evolutionary Computation and Big Data"

Overview

Nowadays, big data has been attracting increasing attention from academia, industry and government. Big data is defined as the dataset whose size is beyond the processing ability of typical databases or computers. Big data analytics is to automatically extract knowledge from large amounts of data. It can be seen as mining or processing of massive data, and “useful” information can be retrieved from large dataset. Big data analytics can be characterized by several properties, such as large volume, variety of different sources, and fast increasing speed (velocity). It is of great interest to investigate the role of evolutionary computing (EC) techniques, including evolutionary algorithms and swarm intelligence algorithms for the optimization and learning involving big data, in particular, the ability of EC techniques to solve large scale, dynamic, and sometimes multi-objective big data analytics problems.

Topics of Interest

This special session aims at presenting the latest developments of EC techniques for big data problems, as well as exchanging new ideas and discussing the future directions of EC for big data. Original contributions that provide novel theories, frameworks, and solutions to challenging problems of big data analytics are very welcome for this Special Session. Potential topics include, but are not limited to:
  1. High-dimensional and many-objective evolutionary optimization
  2. Big data driven optimization of complex engineering systems
  3. Integrative analytics of diverse, structured and unstructured data
  4. Extracting new understanding from real-time, distributed, diverse and large-scale data resources
  5. Big data visualization and visual data analytics
  6. Scalable, incremental learning and understanding of big data
  7. Scalable learning techniques for big data
  8. Big data driven optimization of complex systems
  9. Human-computer interaction and collaboration in big data
  10. Big data and cloud computing
  11. Cross-connections of big data analysis and hardware
  12. Big data techniques for business intelligence, finance, healthcare, bioinformatics, intelligent transportation, smart city, smart sensor networks, cyber security and other critical application areas
  13. MapReduce implementations combined with evolutionary computation or swarm intelligence approaches

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 Big Data.

Important Dates

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

Organisers

Committee Member


Biography of the Proposers

Shi Cheng received the Bachelor's degree in Mechanical and Electrical Engineering from Xiamen University, Xiamen, the Master's degree in Software Engineering from Beihang University (BUAA), Beijing, China, the Ph.D. degree in Electrical Engineering and Electronics from Liverpool University, Liverpool, United Kingdom, the Ph.D. degree in Electrical and Electronic Engineering from Xi’an Jiaotong-Liverpool University, Suzhou, China in 2005, 2008, and 2013, respectively. He is currently a research fellow with Division of Computer Science, University of Nottingham Ningbo, China. He has published more than 30 research articles in peer-reviewed journals and international conferences. His current research interests include swarm intelligence, multiobjective optimization, and data mining techniques and their applications.

Yuhui Shi received the PhD degree in electronic engineering from Southeast University, Nanjing, China, in 1992. He is a Professor in the Department of Electrical and Electronic Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, China. Before joining Xi'an Jiaotong-Liverpool University, he was with Electronic Data Systems Corporation, Indianapolis, IN. His main research interests include the areas of computational intelligence techniques (including swarm intelligence) and their applications. Dr. Shi is the Editor-in-Chief of the International Journal of Swarm Intelligence Research.

Yaochu Jin is currently a Professor of Computational Intelligence with the Department of Computing, University of Surrey, Guildford, U.K., where he heads the Nature Inspired Computing and Engineering Group. He is also a Finland Distinguished Professor awarded by Academy of Finland. His main research interests include computational intelligence, computational neuroscience and computational systems biology, with applications to complex engineering optimization, bioengineering, swarm robotics, and autonomous systems. His current research is funded by EU FP7, UK EPSRC and industries, including Intellas UK, Santander, Aero Optimal, Bosch UK and Honda. He has delivered 20 invited keynote speeches at international conferences. Dr Jin is the founding chair of the IEEE Symposium on Computational Intelligence in Big Data and Guest Editor of the IEEE Computational Intelligence Magazine special issue on Big Data. He is an Associate Editor of several international journals including IEEE TRANSACTIONS ON CYBERNETICS, IEEE TRANSACTIONS ON NANOBIOSCIENCE, and IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE and BioSystems. He is currently Vice President for Technical Activities, and IEEE Distinguished Lecturer. 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.

Bin Li received the B.S. degree from HeFei University of Technology, Hefei, China, in 1992, the M.Sc degree from Institute of Plasma Physics, China Academy of Science, Hefei, China, in 1995, and the Ph.D degree from University of Science and Technology of China, China in 2001. He is currently a professor with the School of Information Science and Technology, University of Science and Technology of China, Hefei, China. He has published more than 50 refereed publications. His major research interests include evolutionary computation, pattern recognition, and real-world applications. Dr. Li is the Founding Chair of IEEE CIS Hefei Chapter, and the founding Counselor of IEEE USTC Student Branch.

Simone Ludwig received the PhD degree from Brunel University, UK, in 2004. She is currently an associate professor at North Dakota State University, USA, conducting research in the area of computational intelligence. In particular, developing novel algorithms to address different optimization problems in the area of data mining (large data) and distributed computing. She has published around 90 peer-reviewed articles both in journals and conference proceedings. Dr. Ludwig has served as a co-chair, track chair, and tutorial chair for different conferences, as well as served on numerous conference program committees. In addition, she currently serves on the editorial board of 3 journals.

Yinan Guo received the PhD degree in control theories and their applications from China University of Mining and Technology, China, in 2003. From September 2000, she worked as a Lecturer, Associate professor and Professor in China University of Mining and Technology respectively. In 2012, she done cooperative research on computational intelligence as an Academic visitor in CERCIA, School of Computer Science, Birmingham University, UK. Her current research interests include interactive evolutionary algorithms, knowledge-inducing cultural algorithm, evolutionary multi-objective optimization, evolutionary dynamic optimizations and relevant real-world applications. Dr Guo has over 70 publications and six research projects in the above domains.

Junfeng Chen received the PhD degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2011. Currently, she is an associate professor in the College of IOT Engineering, Hohai University, Changzhou, China. Her research interests include swarm intelligence, artificial intelligence with uncertainty and big data analytics. She has published over 20 papers in international journals and conference

Friday, 4 December 2015

FUZZ-IEEE 2016 Plenary Speakers

IEEE WCCI 2016 is pleased to announce the following FUZZ-IEEE Plenary Speakers:

  1. James C. Bezdek, IEEE Fellow, 2001 IEEE CIS Fuzzy Systems Pioneer Awardee
  2. Nikhil R. Pal, IEEE Fellow, 2015 IEEE CIS Fuzzy Systems Pioneer Awardee
  3. Frederick E. Petry, IEEE Fellow, 2016 IEEE CIS Fuzzy Systems Pioneer Awardee
  4. Jie Lu, Editor-in-Chief for Knowledge-Based Systems (Elsevier)
  5. Witold Pedrycz, IEEE Fellow, 2013 IEEE CIS Fuzzy Systems Pioneer Awardee

More Plenaries will be announced soon. Visit goo.gl/Rzuazg for more information.

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

Organisers

Hongmei He
h.he@cranfield.ac.uk

Ashutosh Tiwari
A.Tiwari@cranfield.ac.uk

Jörn Mehnen
j.mehnen@cranfield.ac.uk

Tim Watson
tw@warwick.ac.uk

Yaochu Jin
yaochu.jin@surrey.ac.uk

Bogdan Gabrys
BGabrys@bournemouth.ac.uk

Internet of Things (IoT) delivers new value by connecting People, Process and Data. It brings great opportunities and is changing our life style. However, great opportunities also bring large risks that the IoT enabled systems could be threaten with various cyber-attacks, crimes and terrorism, as the IoT enabled systems produce a large cyber space. Hence, cyber security is particularly important in IoT enabled systems, and has raised much attention of researchers and industry recently. Evolutionary Computation and other Computational Intelligence techniques have been applied in various areas, such as computational biology, medical science, finance, engineering, etc. Cyber Security will be another area, where we can explore the power of Evolutional Computation and other Computational Intelligence techniques.

Scope and Topics

This special session will cover the following topics of Cyber Security enabled by Evolutionary Computation and other Computational Intelligence techniques, but not limited.
  • Bio-inspired cyber security architecture
  • Cloud security
  • Web spider defence
  • Biometrics-based authentication
  • Cyber-matrices based authentication
  • Prediction of attacks
  • Detection of spam emails
  • Detection and analysis of malware
  • Autonomous Security
  • Information security
  • Privacy and anonymity
  • Secure protocols
  • Adaptive, secure protocols

Submission

Please follow the IEEE CEC2016 instruction for authors and submit your paper via the IEEE CEC 2016 online submission system (http://ieee-cis.org/conferences/cec2016/upload.php). Please select ‘7az: Evolutionary Computation and Other Computational Intelligence Techniques for Cyber Security’ as the main research topic of your paper.

Important Dates

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

Thursday, 3 December 2015

Call for Papers WCCI 2016 Special Session "Recent Advances in Fuzzy Control System Design and Analysis"

Aim and scope

This special session aims to present state-of-the-art results in the area of theory and applications of fuzzy control system design and analysis, and to get together well-known and potential researchers in this area. Fuzzy control system design and analysis provide a systematic and efficient approach to controlling of nonlinear plants and analysis of nonlinear control systems, and they have been employed to deal with a wide range of nonlinear control systems. However, there is still room for improvement of the existing results in order to propose new techniques for control of nonlinear systems. In this special session, the focus is mainly on the fuzzy control system design and analysis with emphasis on the theory and applications. The important problems and difficulties on the fuzzy control systems will be addressed, their concepts will be provided and methodologies will be proposed to take care of the nonlinear systems using the fuzzy control system

Topics

The main topics of this special session include, but are not limited to:
  • Takagi-Sugeno fuzzy control system
  • Uncertain fuzzy system
  • Fuzzy hybrid system
  • Fuzzy switching system
  • Fuzzy time-delay system
  • Fuzzy stochastic system
  • Fuzzy polynomial system
  • Type-2 fuzzy control system
  • Stability analysis of Takagi-Sugeno fuzzy system
  • Nonlinear control design based on Takagi-Sugeno fuzzy system
  • Predictive control
  • Robust control
  • Sampled-data control
  • Filtering
  • Sliding mode control and observer

Important dates

  • January 15, 2016 - Paper submission deadline
  • March 15, 2016 - Author notification of acceptance or rejection
  • April 15, 2016 - Deadline for receipt of final manuscript

Organized by


Submission details and additional information

  • http://wcci2016.org/
  • http://lendek.net/fuzz-ieee2016ss/
  • http://ieee-cis.org/conferences/fuzzieee2016/upload.php


Call for Papers WCCI 2016 Special Session "Humanlike Learning for Intelligent Systems (Hull 2016)"

Introduction

Machine learning, with the aim of building intelligent systems by learning model or knowledge from data, has achieved great progress in the past 30 years. However, a huge gap of learning ability still exists between machine learning and human learning.

For example, a five year old child can identify objects, understand speech and language via learning from small number of instances or daily communication, whereas machines can hardly match this ability even by learning from big data. In recent years, some researchers have attempted to develop machine learning methods simulating the human learning behavior. Such methods, called as "Humanlike Learning", have some features: learning from small supervised data, interactive, alltime incremental (lifelong), exploiting contexts and the correlation between different data sources and tasks, etc. Some existing learning methods, such as incremental learning, active learning, transfer learning, domain adaptation, learning with use, multitask learning, zeroshot/oneshot learning, can be viewed as special/simplified forms of humanlike learning. The future trend is to make learning methods more flexible and active, requiring less supervision, exploiting all kinds of data more adequately.

Topic

The topics of interest include, but are not limited to:
  • Brain inspired neural networks
  • Human like learning for deep models
  • Hybrid supervised and unsupervised learning
  • Learning from interaction
  • Learning with use
  • Zero/Oneshot learning
  • Advanced transfer learning and adaptation
  • Advanced multitask learning
  • Learning from heterogeneous data
  • Human like learning for pattern recognition, computer vision, robotics and other applications

Important Dates

Submission: January 15th, 2016

Special Session Chairs

Cheng Lin Liu Research Center for Brain inspired Intelligence, Institute of Automation, Chinese Academy of Sciences
Zhaoxiang Zhang   Research Center for Brain inspired Intelligence, Institute of Automation, Chinese Academy of Sciences