## Monday, 30 November 2015

### Call for Papers WCCI 2016 Special Session "Advanced Supervised Learning Techniques and Its Applications"

#### Aim and Scope

IEEE World Congress on Computational Intelligence (IEEE WCCI) which will be held in the magnificent city of Vancouver, Canada. IEEE WCCI has traditionally been the largest technical event in the field of computational intelligence. Over the years the event has provided a platform for highly acclaimed intellectuals from all over the world to discuss and present their research findings on computational intelligence.

As one of the important branches on computational intelligence, supervised learning techniques have been widely used in numerous real-world applications, ranging from information retrieval, multimedia content analysis, web mining, business intelligence to bioinformatics, research expedition, geological surveillance, public security, and so on. Traditional supervised learning makes several simplifying assumptions to facilitate the induction of learning systems, such as the strong supervision assumption that training examples carry sufficient and explicit supervision information, single domain assumption that training examples come from identical domain, uniform distribution assumption that training examples are class-balanced and have equal misclassification costs, etc.

Nonetheless, the above simplifying assumptions may not fully hold in practice due to various constraints imposed by physical environment, problem characteristics, and resource limitations. In recent years, researches on advanced supervised learning techniques have been rapidly growing to meet the increasing need in learning from data under non-trivial environments. The aim of this special session is to bring researchers and practitioners who work on various aspects of advanced supervised learning, to discuss on the state-of-the-art and open problems, to share their expertise and exchange the ideas, and to offer them an opportunity to identify new promising research directions.

#### Topics of Interest

The organizing committee will put in place a rich and varied technical program which is designed to engage participants in cross-fertilization of ideas among diverse areas in supervised learning techniques. We wish we will serve as a good channel to establish new connections and foster everlasting friendship among fellow counterparts. This special session solicits papers whose topics fall into (but not limited to) the following categories:
• Learning from labeled and unlabeled data, such as semi-supervised learning, PU learning, etc.
• Learning from multi-instance data, such as multi-instance learning, multi-instance multi-label (MIML) learning, etc.
• Learning from data with multiple class labels, such as multi-label learning, partial label learning, etc.
• Learning from data from multiple domains, including transfer learning, multi-task learning
• Learning from data with structured outputs
• Applications of advanced machine learning techniques in biometric recognition
• Applications of advanced machine learning in unstructured data analysis, including text, image, video, etc.
• Applications of advance machine learning in cross-disciplinary fields, such as business intelligence, bioinformatics, space physics, astronomy, etc.
• Applications of machine learning in big data, such as research expedition data, astronomy data, remote sensing data, etc.

#### Important Dates

• Paper Submission: January 15, 2016
• Notification of acceptance of papers: March 15th, 2016
• Final Paper & Copyright: April 15, 2016
• Registration : April 15, 2016
• Conference Dates: July 25-29, 2016, Vancouver, CANADA

#### Submission Guidelines

Please kindly refer to the following paper submission guidelines before submitting your papers:
• All special session papers must be submitted through the IEEE WCCI 2016 online submission system and please select respective special session title under the list of research topics in the submission system. Our special session is Advanced Supervised Learning Techniques and Its Application. Such decision will be made by the Special Session Organizers in consultation with the Special Session Chair.
• To help ensure correct formatting, please use the style files for U.S. Letter (http://www.ieee.org/conferences_events/conferences/publishing/templates.html) as template for your submission. These include LaTeX and Word.
• Only papers prepared in PDF format will be accepted.
• Paper Length: Up to 8 pages, including figures, tables and references. At maximum, two additional pages are permitted with overlength page charge of US$125/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). • No page numbers please. We will insert the page numbers for you. Note: Violations of any of the above paper specifications may result in rejection of your paper. Please note that the Latex template does not allow for keywords. If you are using the Latex template, do not include keywords in your paper. If you encounter any problems with the submission of your papers, please contact the IEEE WCCI 2016 Paper Submission Chair Dr. Ke Tang ketang@ustc.edu.cn #### Special Session Co-Chairs Min-Ling Zhang, (Southeast University), zhangml@seu.edu.cn Fuzhen Zhuang, (ICT, CAS), zhuangfz@ics.ict.ac.cn Bing Han (Xidian University), bhan@xidian.edu.cn ### Call for Papers WCCI Special Session "Machine Learning with Incompletely Labeled Data" #### Motivation Traditional supervised learning methods typically require the training data are fully labeled. Nowadays, the data size increases with an unprecedented speed. Fully labeled data becomes infeasible in many real situations, and consequently incomplete labeled data (or data with weak supervision) is ubiquitously existed. For years various approaches have been developed to learn with weak supervision, and learning from big data with weak supervision is showing its superiority to learning with fully labeled yet small data. However, there are still many open problems and in recent years many interesting challenges have been realized. For example, safe semi-supervised learning that prevents unlabeled data hurting the performance is desired; developing data-adaptive active learning strategies have not fully touched; effective partial label learning in the presence of class imbalance data; deriving high quality labels from noisy crowds; borrowing supervision from auxiliary sources, etc. #### Scope The main goal of this session is to provide a forum for researchers in this field to share the latest advantages in theories, algorithms, and applications on learning with incompletely labeled data. Authors are invited to submit their original work on learning with incompletely labeled data. The topics of interest include, but are not limited to: • Semi-supervised learning • Active learning • Partial label learning • Crowdsourcing • Multi-instance learning • Multi-label learning • Multi-instance multi-label learning • Learning with noisy labels • Weak label learning • Transfer learning • Zero-shot learning • Scalable or efficient learning algorithms #### Special Session Chairs Yu-Feng Li, (Nanjing University) liyf@nju.edu.cn Sheng-Jun Huang, (Nanjing University of Aeronautics and Astronautics) huangsj@nuaa.edu.cn Min-Ling Zhang, (Southeast University) zhangml@seu.edu.cn #### Paper Submission Please read the following paper submission guidelines before submitting your papers: All special session papers must be submitted through the IEEE WCCI 2016 online submission system and please select respective special session title under the list of research topics in the submission system. Our special session is Advanced Supervised Learning Techniques and Its Application. Such decision will be made by the Special Session Organizers in consultation with the Special Session Chair. To help ensure correct formatting, please use the style files for U.S. Letter (http://www.ieee.org/conferences_events/conferences/publishing/templates.html) as template for your submission. These include LaTeX and Word. Only papers prepared in PDF format will be accepted. Paper Length: Up to 8 pages, including figures, tables and references. At maximum, two additional pages are permitted with overlength page charge of US$125/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). No page numbers please. We will insert the page numbers for you.

#### Important Dates

Paper submission: 15 Jan 2016 (Please specify our special session ‘Machine Learning with incompletely labeled data’ when you contribute your submission)

Final paper submission: 15 Apr 2016

http://lamda.nju.edu.cn/conf/ijcnn16-ILD/#

### Call for Papers WCCI 2016 Special Session "Smart Educational Techniques in Big Data Age"

Submission System: http://www.wcci2016.org/submission.php

Accepted papers will appear in the IJCNN/WCCI 2016 proceedings to be published by IEEE.

#### Important Dates

Paper Submission Due:         15/01/2016

#### Conference Scope

Data mining provides educational institutions the capability to explore, visualize and analyze large amounts of data in order to reveal valuable patterns in students' learning behaviors without having to resort to traditional survey methods. Turning raw data into useful information and knowledge also enables educational institutions to improve teaching and learning practices, and to facilitate the decision-making process in educational settings. Thus, it is becoming important for researchers to exploit the abundant data generated by various educational systems for enhancing teaching, learning and decision making.

In addition, the development and training of teachers in regional area can be also improved by adopting smart techniques in the big data age. How to get these tasks done smartly and effectively is another important issue that could be potentially addressed in Big data age.

#### Topics of Interest

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

1. Data mining in education
• Learning analytics
• "Big Data" applications and opportunities in learning and education
• Integrating data mining and pedagogical theory
• Data mining with emerging pedagogical environments such as educational games and MOOCs
2. Smart Educational Techniques
• Recommender systems for learning
• Case studies in Educational Data
• Data Driven Performance Evaluation

#### Paper Submissions

Manuscripts submitted to special sessions should be done through the paper submission website of IEEE WCCI 2016.

http://www.wcci2016.org/submission.php

Please make sure that papers submitted to their special session clearly indicate the name of the special session the paper belongs to.

Main Research Topic: "Ti: Smart Educational Techniques in Big Data Age"

All papers submitted to special sessions will be subject to the same peer-review procedure as the regular papers.

#### Organizers

Dr Guandong Xu, University Technology Sydney, Australia
Dr Gang Li, Deakin University, Australia
Dr Wu He, Old Dominion University, USA

### Call for Papers WCCI 2016 Special Session Concept Drift, Domain Adaptation & Learning in Dynamic Environments"

One of the fundamental goals in computational intelligence is to achieve brain-like intelligence, a remarkable property of which is the ability to incrementally learn from noisy and incomplete data, and ability to adapt to changing environments. The special session aims at presenting novel approaches to incremental learning and adaptation to dynamic environments both from the more traditional and theoretical perspective of computational intelligence and from the more practical and application-oriented one.

This Special Session aspires at building a bridge between academic and industrial research, providing a forum for researchers in this area to exchange new ideas with each other, as well as with the rest of the neural network & computational intelligence community.

#### Topics

Papers must present original work or review the state-of-the-art in the following non-exhaustive list of topics:
• Methodologies, algorithms and techniques for learning in dynamic/non-stationary environments
• Incremental learning, lifelong learning, cumulative learning
• Semi-supervised learning methods for handling concept-drift
• Ensemble methods for learning under concept drift
• Learning under concept drift and class unbalance
• Change-detection tests and anomaly-detection algorithms
• Algorithms for information mining in nonstationary datastreams
• Applications that call for learning in dynamic/non-stationary environments, and for incremental learning, such as:
• Adaptive classifiers for concept drift and recurring concepts
• Intelligent systems operating in dynamic/non-stationary environments
• Intelligent embedded and cyber-physical systems
• Applications that call for change and anomaly detection, such as:
• fault detection
• fraud detection
• network-intrusion detection and security
• intelligent sensor networks
• Cognitive-inspired approaches to adaptation and learning
• Development of test-sets benchmarks for evaluating algorithms learning in non-stationary/dynamic environments
• Issues relevant to above mentioned or related fields

#### Keywords

Concept drift, nonstationary environment, change/anomaly detection, domain adaptation, incremental learning, data streams.

#### Paper Submission

THE DEADLINE FOR THE PAPER SUBMISSION TO THE SPECIAL SESSION IS THE SAME OF IEEE WCCI 2016, January 15th 2016.

All the submissions will be peer-reviewed with the same criteria used for other contributed papers.

Perspective authors will submit their papers through the IEEE IJCNN/WCCI 2016 conference submission system at http://www.wcci2016.org/

Please make sure to select the Special Session nr 26 "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" from the "S. SPECIAL SESSION TOPICS" name in the "Main Research topic" dropdown list;

Templates and instruction for authors will be provided on the IEEE IJCNN/WCCI webpage http://www.wcci2016.org/

All papers submitted to the special sessions will be subject to the same peer-review procedure as regular papers, accepted papers will be published in the conference proceedings.

Further information about IEEE IJCNN/WCCI 2016 can be found at http://www.wcci2016.org/

For any question you may have about the Special Session or paper submission, feel free to contact Giacomo Boracchi

#### IMPORTANT DATES

Paper submission: January 15th, 2016
Paper Decision notification: March 15th, 2016
Conference Dates: July 25 - 29th, 2016

#### Organizes

• Giacomo Boracchi (Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Italy)
• Robi Polikar (Rowan University, Glassboro, NJ, USA)
• Manuel Roveri (Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Italy)
• Gregory Ditzler, (University of Arizona, AZ, USA)

#### Technical Program Committee

• Alfred Bifet, University of Waikato, New Zealand
• Gianluca Bontempi, UniversitÃ© Libre de Bruxelles, Belgium
• Yaochu Jin, University of Surrey, England, UK
• Georg Krempl, University Magdeburg, Germany
• Ludmilla Kuncheva, University of Bangor, Wales, UK
• Leandro L. Minku, University of Birmingham, UK
• Harris Papadopoulos, Frederick University, Cyprus
• Leszek Rutkowski, Czestochowa University of Technology, Poland
• Shiliang Sun, East China Normal University
• Marley Vellasco, PontifÃ­cia Universidade CatÃlica do Rio de Janeiro, Brasil
• Shengxiang Yang, Brunel University, England, UK

### Call for Papers WCCI 2016 Special Session "Intelligent Medical Science"

The purpose of this special session is to disseminate and discuss recent and significant research issues on how intelligent methodologies can be used to solve challenging problems related to medical, biomedical, and healthcare fields. This special session will be held under IEEE CIS Task Force of "Fuzzy Logic in Medical Sciences".

#### Topics of interest

• Fuzzy logic-based medical diagnosis control system
• Fuzzy logic-based biomedical applications
• Soft computing for biomedical applications
• Fuzzy logic-based affective computing and psychological evaluations
• Fuzzy data analysis – bioinformatics, medical informatics, pattern recognition
• Fuzzy optimization and control
• Fuzzy machine learning approach to biomedical applications
• Neuro-fuzzy models for biomedical signal processing
• Signal processing of MRI, fMRI, EEG, ECG, etc.
• Smart diagnostic predictions of various diseases
• Applications in image processing and pattern recognition
• Fuzzy logic vs. other soft computing approaches
• Approaches based on neuro-fuzzy, evolutionary neuro-fuzzy, neuro-genetic, genetic fuzzy, fuzzy cognitive map
• Fuzzy inference systems
• Assistive robotics
• Fuzzy temporal representation of knowledge

#### Paper submission

All papers must be submitted through the IEEE WCCI FUZZ 2016 online submission system. There, please make sure to select the appropriate special session title (FUZZ-IEEE-20 Intelligent Medical Science) under the list of research topics in the submission system. More detailed submission instructions and paper templates can be found on the WCCI submission page.

#### Important dates

Paper submission deadline:   January 15, 2016
Paper decision notification:   March 15, 2016
Final paper submission and registration deadline:   April 15, 2016
WCCI 2016:   July 25-29, 2016

#### Organisers

Syoji Kobashi
University of Hyogo
Japan
kobashi@eng.u-hyogo.ac.jp

Gerald Schaefer
Loughborough University
United Kingdom
gerald.schaefer@ieee.org

Hiroharu Kawanaka
Mie University
Japan
kawanaka@elec.mie-u.ac.jp

Atsushi Inoue
Eastern Washington University
USA
inoueatsushij@gmail.com

### Call for Papers WCCI 2016 Special Session "Reinforcement Learning and Approximate Dynamic Programming for Optimization in Dynamic Environment"

Reinforcement learning and approximate dynamic programming can be used to address learning and optimization problems in many areas of engineering and science, including artificial intelligence, control engineering, operation research, psychology, and economy. They have provided critical tools to solve some engineering and science problems in modern complex systems. However, there still exist some challenges in the applications of reinforcement learning and approximate dynamic programming to academic and industrial problems such as the curse of dimensionality and optimization in dynamic environment. At the same time, the development of new technologies such as quantum technology and deep learning provides a remarkable opportunity to revisit these challenges in reinforcement learning and approximate dynamic programming. This special session will focus on relevant topics of reinforcement learning and approximate dynamic programming, and provide a forum for idea exchange in the emerging research area.

#### Scope and Topics

The aim of this special session will be to provide an account of the state-of-the-art in this fast moving and cross-disciplinary field of reinforcement learning and approximate dynamic programming. It is expected to bring together the researchers in relevant areas to discuss latest progress, propose new research problems for future research. All the original papers related to reinforcement learning (RL) and approximate dynamic programming (ADP) are welcome. Topics of interest include but are not limited to:
• Policy iteration algorithm
• hierarchical reinforcement learning
• multi-agent reinforcement learning
• deep reinforcement learning
• quantum reinforcement learning applications of ADP and RL to optimization in dynamic environment

#### Paper Submission

Perspective authors should submit their papers through the IEEE IJCNN/WCCI 2016 conference submission system at http://www.wcci2016.org/

Templates and instruction for authors will be provided on the IEEE IJCNN/WCCI webpage http://www.wcci2016.org/

Please make sure to select the Special Session IJCNN-29 “Reinforcement Learning and Approximate Dynamic Programming for Optimization in Dynamic Environment” from the “S. SPECIAL SESSION TOPICS” name in the “Main Research topic” dropdown list;

All the submissions to the special sessions will be subject to the same peer-review procedure as regular papers, and accepted papers will be published in the conference proceedings.

Further information about IEEE IJCNN/WCCI 2016 can be found at http://www.wcci2016.org/
For any question you may have about the Special Session or paper submission, feel free to contact the organizers of this Special Session.

#### Important Dates

Paper submission: January 15th, 2016
Paper Decision notification: March 15th, 2016
Conference Dates: July 25 - 29th, 2016

#### Organizers

Dr Daoyi Dong
Senior Lecturer, School of Engineering and Information Technology, University of New South Wales, Australia
E-mail: daoyidong@gmail.com

Prof Dongbin Zhao
Professor, Institute of Automation, Chinese Academy of Sciences, China
E-mail: dongbin.zhao@ia.ac.cn

A/Prof Qinmin Yang
Associate Professor, Department of Control Science and Engineering, Zhejiang University, China
E-mail: qmyang@iipc.zju.edu.cn

## Sunday, 29 November 2015

### Call for Papers WCCI 20166 Special Session on Computational Intelligence in Bioinformatics (CIB)

Bioinformatics, computational biology, and bioengineering present a number of complex problems with large search spaces. Recent applications of Computational Intelligence (CI) in this area suggest that they are well-suited to this area of research. This special session will highlight applications of CI to a broad range of topics. Particular interest will be directed towards novel applications of CI approaches to problems in these areas. The scope of this special session includes evolutionary computation, neural computation, fuzzy systems, artificial immune systems, swarm intelligence, ant-colony optimization, simulated annealing, and other CI methods or hybridizations between CI approaches. Applications of these CI methods to bioinformatics, computational biology, and bioengineering problems are the main focus of this hybrid special session. There is a clear interest in both the Computational Intelligence community and Biology communities for this special session. This hybrid special session is sponsored by the IEEE CIS BBTC (Computational Intelligence Society - Bioinformatics and Bioengineering Technical Committee).
Particular interest will be directed towards novel applications of computational intelligence to problems in these areas.

#### Topics

Papers must present original work or review the state-of-the-art in the following non-exhaustive list of topics:
• Analysis and visualization of large biological data sets
• Biological and medical ontologies
• Biomedical data modelling and mining
• Biomedical model parameterization
• Brain computer interface
• Computational proteomics
• Systems Biology
• Ecoinformatics and applications to ecological data analysis
• Emergent properties in complex biological systems
• Gene expression array analysis
• Gene finding
• Genetic networks
• High-throughput data analysis
• Immuno- and chemo-informatics
• In-silico optimization of biological systems
• Medical image analysis
• Medical imaging and pattern recognition
• Medicine and health informatics
• Metabolic pathway analysis
• Microarray design or oligonucleotide selection
• Modelling, simulation and optimization of biological systems
• Molecular docking and drug design
• Molecular evolution and phylogenetics
• Molecular sequence alignment and analysis
• Motif and signal detection
• Robustness and evolvability of biological networks
• Single nucleotide polymorphism (SNP) analysis
• Structure prediction and folding
• Systems and synthetic biology and
• Treatment optimization.

#### IMPORTANT DATES

Paper submission:  January 15th, 2016
Paper Decision notification: March 15th, 2016
Conference Dates: July 25 - 29th, 2016

THE DEADLINE FOR THE PAPER SUBMISSION TO THE SPECIAL SESSION IS THE SAME OF WCCI 2016, January 15th 2016.

The special session on Computational Intelligence in Bioinformatics is soliciting high quality papers of original research and application papers that have not been published elsewhere and are not under consideration for publication elsewhere. Manuscripts should be prepared according to the standard format and page limit of regular papers specified in the WCCI 2016 website. All papers will be rigorously reviewed by at least two reviewers. Accepted papers will be treated in the same way as regular papers and published in the WCCI 2016 conference proceedings.

Further information about WCCI 2016 can be found at
http://www.wcci2016.org/
and about the special session at
http://vpp.users.uth.gr/CIB-WCCI-2016/

#### Organizers

Dr. Vassilis Plagianakos, Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece.
Prof. Roberto Tagliaferri, Dipartimento di Scienze Aziendali - Management & Innovation Systems/DISA-MIS, University of Salerno, Fisciano, Italy

## Saturday, 28 November 2015

### IEEE Transactions on Evolutionary Computation, Volume 19, Number 6, December 2015

1. A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization
Author(s): Zhang, X. ; Tian, Y. ; Jin, Y.
Page(s): 761 - 776

2. Switch Analysis for Running Time Analysis of Evolutionary Algorithms
Author(s): Yu, Y. ; Qian, C. ; Zhou, Z.
Page(s): 777 - 792

3. A Boltzmann-Based Estimation of Distribution Algorithm for a General Resource Scheduling Model
Author(s): Liang, X. ; Chen, H. ; Lozano, J.A.
Page(s): 793 - 806

4. An Estimation of Distribution Algorithm With Cheap and Expensive Local Search Methods
Author(s): Zhou, A. ; Sun, J. ; Zhang, Q.
Page(s): 807 - 822

5. Gene Regulatory Network Evolution Through Augmenting Topologies
Author(s): Cussat-Blanc, S. ; Harrington, K. ; Pollack, J.
Page(s): 823 - 837

6. A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling
Author(s): Cheng, R. ; Jin, Y. ; Narukawa, K. ; Sendhoff, B.
Page(s): 838 - 856

7. Evolutionary Nonlinear Projection
Author(s): Ashlock, D. ; McEachern, A.
Page(s): 857 - 869

8. A Hybrid Swarm-Based Approach to University Timetablinga
Author(s): Fong, C.W. ; Asmuni, H. ; McCollum, B.
Page(s): 870 - 884

9. Using Learning Classifier Systems to Learn Stochastic Decision Policies
Author(s): Chen, G. ; Douch, C.I.J. ; Zhang, M.
Page(s): 885 - 902

10. Network Structural Balance Based on Evolutionary Multiobjective Optimization: A Two-Step Approach
Author(s): Cai, Q. ; Gong, M. ; Ruan, S. ; Miao, Q. ; Du, H.
Page(s): 903 - 916

### IEEE Transactions on Fuzzy Systems, Volume 23, Number 6, December 2015

1. Multiattribute Decision Making Based on Interval-Valued Intuitionistic Fuzzy Sets, PSO Techniques, and Evidential Reasoning Methodology
Author(s): Chen, S. ; Chiou, C.
Page(s):1905 - 1916

2. Multistep Fuzzy Bridged Refinement Domain Adaptation Algorithm and Its Application to Bank Failure Prediction
Author(s): Behbood, V. ; Lu, J. ; Zhang, G. ; Pedrycz, W.
Page(s):1917 - 1935

3. Fuzzy Planar Graphs
Author(s): Samanta, S. ; Pal, M.
Page(s):1936 - 1942

4. State and Output Feedback Control of Interval Type-2 Fuzzy Systems With Mismatched Membership Functions
Author(s): Li, H. ; Sun, X. ; Wu, L. ; Lam, H.K.
Page(s):1943 - 1957

5. A Decision-Theoretic Rough Set Approach for Dynamic Data Mining
Author(s): Chen, H. ; Li, T. ; Luo, C. ; Horng, S. ; Wang, G.
Page(s):1958 - 1970

6. Introducing the Fuzzy Relational Hybrid Model as a Building Block for Intelligent Modeling of Hybrid Dynamical Systems
Author(s): Aghili-Ashtiani, A. ; Menhaj, M.B.
Page(s): 1971 - 1983

7. A Fuzzy Logic-Based Retrofit System for Enabling Smart Energy-Efficient Electric Cookers
Author(s): Ghelli, A. ; Hagras, H. ; Aldabbagh, G.
Page(s): 1984 - 1997

8. Adaptive Fuzzy Tracking Control of Nonlinear Time-Delay Systems With Dead-Zone Output Mechanism Based on a Novel Smooth Model
Author(s): Liu, Z. ; Lai, G. ; Zhang, Y. ; Chen, C.L.P.
Page(s): 1998 - 2011

9. A Novel Optimal Robust Control Design of Fuzzy Mechanical Systems
Author(s): Zhen, S. ; Zhao, H. ; Huang, K. ; Deng, B. ; Chen, Y.
Page(s): 2012 - 2023

10. Fast Fuzzy Pattern Tree Learning for Classification
Author(s): Senge, R. ; Hullermeier, E.
Page(s): 2024 - 2033

11. Quantitative Computation Tree Logic Model Checking Based on Generalized Possibility Measures
Author(s): Li, Y. ; Ma, Z.
Page(s): 2034 - 2047

12. Recurrent Classifier Based on an Incremental Metacognitive-Based Scaffolding Algorithm
Author(s): Pratama, M. ; Anavatti, S.G. ; Lu, J.
Page(s): 2048 - 2066

13. Design of a Polynomial Fuzzy Observer Controller With Sampled-Output Measurements for Nonlinear Systems Considering Unmeasurable Premise Variables
Author(s): Liu, C. ; Lam, H.K.
Page(s): 2067 - 2079

14. An Evolving Interval Type-2 Neurofuzzy Inference System and Its Metacognitive Sequential Learning Algorithm
Author(s): Das, A.K. ; Subramanian, K. ; Sundaram, S.
Page(s): 2080 - 2093

15. 2-Additive Capacity Identification Methods From Multicriteria Correlation Preference Information
Author(s): Wu, J. ; Yang, S. ; Zhang, Q. ; Ding, S.
Page(s): 2094 - 2106

16. Bifuzzy Discrete Event Systems and Their Supervisory Control Theory
Author(s): Deng, W. ; Qiu, D.
Page(s): 2107 - 2121

17. Discovering Latent Semantics in Web Documents Using Fuzzy Clustering
Author(s): Chiang, I. ; Liu, C.C. ; Tsai, Y. ; Kumar, A.
Page(s): 2122 - 2134

18. Skewness of Fuzzy Numbers and Its Applications in Portfolio Selection
Author(s): Li, X. ; Guo, S. ; Yu, L.
Page(s): 2135 - 2143

19. Determinization of Fuzzy Automata by Means of the Degrees of Language Inclusion
Author(s): Micic, I. ; Jancic, Z. ; Ignjatovic, J. ; Ciric, M.
Page(s): 2144 - 2153

20. Generalizations of OWA Operators
Author(s): Mesiar, R. ; Stupnanova, A. ; Yager, R.R.
Page(s): 2154 - 2162

21. Fuzzy Restricted Boltzmann Machine for the Enhancement of Deep Learning
Author(s): Chen, C.L.P. ; Zhang, C. ; Chen, L. ; Gan, M.
Page(s): 2163 - 2173

22. An Interval-Based Framework for Fuzzy Clustering Applications
Author(s): Silva, L. ; Moura, R. ; Canuto, A.M.P. ; Santiago, R.H.N. ; Bedregal, B.
Page(s): 2174 - 2187

23. A New Fuzzy Cognitive Map Structure Based on the Weighted Power Mean
Author(s): Rickard, J.T. ; Aisbett, J. ; Yager, R.R.
Page(s): 2188 - 2201

### Aim

Ecological informatics and the related field of ecological modelling involve constructing computational models of ecological systems. Environmental modelling is closely related and involves constructing models of the physical environment that biological eco-systems inhabit. The amount of data describing global and local environments and the eco-systems that inhabit them is rapidly increasing. As these are highly-complex systems, algorithms from the field of computational intelligence have already been widely applied to modelling this data. The aim of this special session is to provide a forum for recent research in the application of computational intelligence in the areas of ecological informatics, ecological modelling and environmental modelling. This is a highly topical area and is open to a broad array of methods from the field of computational intelligence.

### Scope

The scope of the special session includes, but is not limited to, the following topics:
• Species distribution and ecological niche modelling
• Predicting species abundance
• Remote sensing image analysis and content-based image retrieval for Ecological Informatics and Environmental Modelling
• Analysis of species assemblages
• Classification of species
• Environmental impact assessment
• Modelling of environmental events including floods
• Issues in the preparation of ecological data for modelling
• Modelling of pollutants or contamination in air, land or water
• Modelling water quality
• Greenhouse gas emissions modelling and the effects of climate change
• Modelling the future development of populations
• Detecting landscape features
• Modelling water drainage systems
• Assessment of habitat quality
• Forecasting of algal blooms
• Habitat suitability modelling
• Predicting crop hazards, pests or diseases
• Modelling interactions between multiple species
• Identifying landscape features
• Modelling ecosystem biomass
• Learning of phenological patterns

### 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

Paper Submission As this is a cross-disciplinary special session, please submit papers via the IEEE CEC 2016 submission site: http://ieee-cis.org/conferences/cec2016/upload.php Please make sure you select "Computational Intelligence in Ecological Informatics and Environmental Modelling" under "Cross-Disciplinary and CI Applications Special Sessions" as the Main Research Topic of your submission. Accepted papers will be published in the conference proceedings that are most appropriate for the paper (IJCNN, FUZZ-IEEE or CEC). This decision will be made by the Special Session Organisers in consultation with the Special Session Chair and one of the three Conference Chairs.

### Organisers

• Dr Michael J. Watts, Auckland Institute of Studies, Auckland, New Zealand. mjwatts@ieee.org
• Professor Jie Yang, Shanghai Jiao Tong University, Shanghai, China, jieyang@sjtu.edu.cn

#### Dr Michael J. Watts

Dr Michael J. Watts (Senior Member, IEEE) is the Academic Head of Programme for Information Technology at Auckland Institute of Studies, Auckland, New Zealand. His research interests are in the areas of ecological informatics, neural networks, neuro-fuzzy systems, and evolutionary algorithms. He is particularly interested in the intersections of these areas, where computational intelligence methods can be applied to ecological informatics. He has published more than 70 peer-reviewed papers in a range of international journals and conferences on a variety of topics, particularly computational intelligence and ecological informatics. He is currently on the editorial boards of the Springer journal Soft Computing and the IEEE Transactions on Neural Networks and Learning Systems. He teaches basic database engineering, fundamentals of programming, data mining and information security and serves on a number of committees of the IEEE Computational Intelligence Society including the Neural Networks Technical Committee and the Standards Committee.

#### Professor Jie Yang

Jie Yang is the Professor and Director of the Institute of Image Processing and Pattern recognition in Shanghai Jiao Tong University. He received a bachelor’s degree in Automatic Control in Shanghai Jiao Tong University, where a master’s degree in Pattern Recognition & Intelligent System was achieved three years later. In 1994, he received Ph.D. at Department of Computer Science, University of Hamburg, Germany. He is the principal investigator of more than 30 national and ministry scientific research projects in image processing, pattern recognition, data mining, and artificial intelligence, including two national 973 research plan projects, three national 863 research plan projects, three National Nature Foundation projects, five international cooperative projects with France, Korea, Japan, New Zealand. He has published four books and more than four hundred articles in national or international academic journals and conferences. Up to now, he has supervised 4 postdoctoral, 32 doctors and 55 masters, and been awarded five research achievement prizes from ministry of Education, China and Shanghai municipality. One Ph.D. dissertation he supervised was evaluated as "National Best Ph.D. Dissertation" in 2009. Two Ph.D. dissertations he supervised were evaluated as "Shanghai Best Ph.D. Dissertation" in 2009 and 2010. He has owned 25 patents.

### WCCI 2016 Workshop Key Challenges and Future Directions of Evolutionary Computation

Organised by:
Yun Li, University of Glasgow, UK (Chair)
Cesare Alippi, Politecnico di Milano, Italy (Vice President for Education, IEEE Computational Intelligence Society)
Thomas Bäck, Universiteit Leiden, The Netherlands (Editor, Handbook of Evolutionary Computation)
Piero Bonissone, Formerly Chief Scientist of GE Global Research, USA (WCCI'16 Workshops Chair)
Stefano Cagnoni, Università degli Studi di Parma, Italy (Secretary, AI*IA)
Carlos Coello Coello, CINVESTAV-IPN, Mexico (Associate Editor, IEEE Trans Evolutionary Computation)
Kalyanmoy Deb, Michigan State University, USA (Associate Editor, IEEE Trans Evolutionary Computation)
David Fogel, Natural Selection Inc, USA (Founding Editor-in-Chief, IEEE Trans Evolutionary Computation)
Marouane Kessentini, University of Michigan, USA (WCCI'16 CEC Tutorial organiser)
Yuhui Shi, Xi'an Jiaotong-Liverpool University, China (WCCI'16 CEC Technical Chair)
Xin Yao, University of Birmingham, UK (President, IEEE Computational Intelligence Society)
Mengjie Zhang, Victoria University of Wellington, New Zealand (WCCI'16 CEC Special Sessions Chair)

Motivation:
Since the first WCCI taking place in Orlando in 1994, this Congress series and the Evolutionary Computation community have progressed tremendously. A number of CEC Panel Sessions were held and explored future directions of Evolutionary Computation. As part of the forthcoming WCCI, CEC 2016 in Vancouver promises c.50 Special Sessions, covering comprehensive activities. A Workshop to explore "Key Challenges and Future Directions of Evolutionary Computation" and to reach consensus among academia and industry is therefore timely. This format (instead of a discussion-only forum or panel session) will allow position papers that are submitted, peer reviewed and duly accepted to be recorded in the CEC Workshop Proceedings for future references.

The Workshop:
Following individual presentations of accepted position papers, small breakout sessions will be held in parallel to explore deeper and broader views. Then an open panel discussion will proceed for convergence among academia and industry. It is intended that a short summary will be written up later for IEEE Computational Intelligence Magazine as a separate article for the CIS community and beyond.

Main Topics:
You are warmly invited to submit a position paper with rationale, rigour and supporting evidence on one or more of the following aspects
• key challenges in Evolutionary Computation (such as NP-complexity, constraint handling, convergence proof, convergence vs robustness, optimality vs robustness, multi-/many-objectives, benchmarks, benchmarking problems);
• future directions of Evolutionary Computation (such as multi-modal optimisation, non-stationary evolution, multi-rate or learning evolution, variable-size or fuzzy evolution, distributed and concurrent optimisation, cloud-based evolution, automated design and customisation, optimal evolution, predictive evolution, hybrid ecological and cultural evolution, quantum and analogue 'evolutionary computation');
• real-world challenges to applications of Evolutionary Computation (such as application demand vs supply, real-world NP-hardest problems, landscape forecasting, complexity reduction, generational evolution vs interactive learning, real-time issues, streaming evolution, ease of implementation, scalability and parallelism, big data application);
• and their emergence and trending behaviours (such as Thomson Reuters' "Hot Topics", "Research Fronts" and "Essential Science Indicators").

Technical Requirements:
You position paper should be academic and should normally contain
1. An introduction - clearly identifying the issue and your position, and written in a way that catches the reader's attention
2. A perspective - based on critical reviews, and providing facts for a solid foundation of your arguments
3. A statement of your position or the challenge - formulating and limiting your chosen issue or argument carefully; supporting or validating your position through inductive reasoning with statistical data, authoritative references, or interviews with industrialist experts; analysing opportunities and threats
4. A discussion of both sides of the issue - examining the strengths and weaknesses of your position and potential alternatives
5. Perceived milestones - suggesting courses of action that you have deduced for future developments or in addressing their challenges
6. Potential impacts - evaluating possible solutions and their impacts on the subject, the field and the wider world
7. A conclusion - summarising and reinforcing (without repeating the introduction or body of the paper) the main points, millstones and impacts that you have formulated and advocated.

Submission:

Publication:
Your position paper will be reviewed by a cross-disciplinary international programme committee, mainly comprising the organisers of this Workshop.  Accepted academic papers will be published in the CEC Workshop Proceedings. Further, it is intended that the summative discussion will be written up for the IEEE Computational Intelligence Magazine following the Workshop.

Biography of the Chair:
Yun Li is Professor of Systems Engineering at University of Glasgow. He received his PhD in parallel computing and control from University of Strathclyde in 1990. Following a period as Consultant Engineer with UK National Engineering Laboratory in 1989 and as post-doctoral Research Engineer with Industrial Systems and Control Ltd in 1990, he joined University of Glasgow as Lecturer in 1991. Dr Li developed a "Neural and Evolutionary Computing" course in 1995 and a popular online interactive courseware GA Demo in 1997.  In 1998, he established and chaired the IEEE CACSD Evolutionary Computation Working Group. He also established the European Network of Excellence in Evolutionary Computing (EvoNet) workgroup on systems, control and drives, and served on the EvoNet Management Board. In 2011, Professor Li went to Singapore as Founding Director to establish and lead University of Glasgow Singapore, the first overseas subsidiary in the University's 560-year history. He has over 200 publications, one of which is elected by Thomson Reuters into "Research Front in Computer Science", one into "Research Front in Engineering", four into "Essential Science Indicators" (ESI), one has been the most popular paper in IEEE Trans Control Systems Technology every month since publication in 2005, and one among the five most popular in IEEE Trans Systems, Man & Cybernetics - B. Professor Li is also the University's third "Top Author", an Associate Editor of IEEE Trans Evolutionary Computation and other journals, a Chartered Engineer in the UK, and an overseas referee for China's "Yangtze River Scholars Program" and Singapore's National Research Foundation and Ministry of Education.

## Friday, 27 November 2015

### Call for Papers WCCI 2016 Special Session on Computational Intelligence in Marketing and Social Sciences (CIMSS 2016)

#### Scope:

Computational intelligence has a long history of applications to marketing and plays an important role in establishing the interdisciplinary pool of methodologies employed in marketing science research. For example, evolutionary algorithms, artificial neural networks, support vector machines and fuzzy logic have been used in demand forecasting, direct marketing and cross selling, among others. Expert systems have been used for decision support in brand management, and data mining has become a core component of customer relationship management in marketing. Likewise, the use of computational intelligence in social science research allows heightened understanding of the dynamics of complex systems. Agent-based modelling, using agents whose intelligence includes full-blown creativity thanks to their ability to learn and to adapt, is revealing information about such systems that has never before been supported.

The purpose of this special session is to bring together the computational intelligence community as well as researchers from marketing and social sciences to set up visions on how state-of-art computational intelligence techniques can be and are used for insightful marketing and social science analysis, and how marketing and social scientists can contribute in promoting new applications with computational intelligence.

#### Topics:

We invite submissions of original, previously unpublished papers with topics on, but not limited to, the following:

Technical issues include (but not limited to)
• Evolutionary Algorithms
• Artificial Neural Networks
• Support Vector Machines/Support Vector Regression
• Fuzzy Logic
• Expert Systems
• Data Mining
• Knowledge Discovery
• Machine Learning
• Agent Based Modelling

Issues of marketing and social sciences include (but not limited to)
• Sales/Demand Forecasting
• Response Modelling
• Retailing and Pricing
• Customer Relationship Management
• Brand Management
• Social Marketing
• Cognitive and Behavioural Sciences
• Computational Social Science
• Politics, Public Policy and Law

### Important Dates:

Full Paper Submission: January 15, 2016

### Submission:

See http://www.wcci2016.org/submission.php (please select “Computational Intelligence in Marketing and Social Sciences” as the main research topic)

### Publication:

Papers submitted to this cross-disciplinary special session of CIMSS (if accepted and presented) will be published in one of the three conference proceedings (IJCNN, FUZZ-IEEE or IEEE CEC) that is deemed most appropriate based on the topic(s). The decision will be made by the special session organisers in consultation with the Special Session Chair and one of the three Conference Chairs.

### Special Session Organisers:

Raymond Chiong (Raymond.Chiong@newcastle.edu.au), The University of Newcastle, Australia
Yukun Bao (yukunbao@hust.edu.cn), Huazhong University of Science and Technology, China
Manuel Chica (manuel.chica@softcomputing.es), European Centre for Soft Computing, Spain
Sergio Damas (sergio.damas@softcomputing.es), European Centre for Soft Computing, Spain

## Thursday, 26 November 2015

### Call for Papers WCCI 2016 Special Session on Linguistic Summarization and Description of Data

Organized by Nicolas Marin, Daniel Sanchez, Anna Wilbik, and Rui Jorge Almeida
http://decsai.ugr.es/pi/lidvis/cfpfuzzieee2016.html

Linguistic summaries and descriptions of data aim to extract and represent knowledge in the form of a collection of natural language sentences. The objective is to obtain a text, as if it was produced by a human expert, describing the most relevant aspects of data for a certain user in a specific context. Automatic generations of data summaries have gained increased relevance with the advent of possibilities to store and acquire data as well as relations between them. In this realm, not only specialized users (e.g. in decision support systems) are interested in this type of approach, but nonspecialized users also show interest in receiving understandable information that is supported by data.

Linguistic summaries commonly use fuzzy set theory to model linguistic variables and incorporate different forms of imprecision in a collection of natural language sentences. In many approaches they can be considered as quantifier based sentences, hence linguistic summaries constitute a perfect application for new developments in the domain of fuzzy quantifiers. Furthermore, linguistic summaries have been related to fuzzy rule systems. Linguistic summaries and description of data is related to other research areas such as knowledge discovery in databases and intelligent data analysis, flexible query answering systems for data, human-machine interaction, uncertainty management, heuristics and metaheuristics, natural language generation or processing. More recently, this field has been related to different paradigms, namely the linguistic description of complex phenomena and computing with words paradigms.

The objective of this special session is to provide a forum for researchers, from the above indicated areas, to present recent developments in linguistic summarizes and description of data as well as discuss how these different approaches can complement each other for the task of building such systems.

The session continues the series of special sessions on the topic organized by some of the organizers of this session in past conferences (IFSA 2015, FUZZ-IEEE 2015).

Topics of interest include, but are not restricted to:
• Protoforms and fuzzy concepts for the linguistic summaries and fuzzy description.
• Quality assessment of linguistic summaries and fuzzy description.
• Techniques and algorithms for generating linguistic summaries and descriptions of data.
• Ontologies for data summarization.
• Logical approaches for modeling linguistic expressions.
• Modeling uncertainty for linguistic summaries and fuzzy description.
• User preference/interest modeling for linguistic summaries and fuzzy description.
• Applications of linguistic summaries and fuzzy description.
• Natural language generation for data summarization.
• Machine Learning applied to data summarization.
• Linguistic information extraction from visual information
• Context-awareness in data summarization and description, and natural languageb generation.

#### Important dates:

Paper submission: January 15th, 2016
Notification of acceptance: March 15th, 2016
Final paper submission: April 15th, 2016
Early registration deadline: April 15th, 2016
Conference: July 25-29, 2016
Instructions for authors, submission and more details in the Conference website: http://www.wcci2016.org/

Accepted papers to this special session (if presented at the Conference) will be published in the conference proceedings of FUZZ-IEEE published by the IEEE.

### Organizers:

Nicolas Marin. Department of Computer Science and Artificial Intelligence, University of Granada
e-mail: nicm@decsai.ugr.es

Daniel Sanchez. Department of Computer Science and Artificial Intelligence, University of Granada.
e-mail: daniel@decsai.ugr.es

Anna Wilbik. Information Systems, School of Industrial Engineering, Eindhoven University of Technology e-mail: a.m.wilbik@tue.nl

Rui Jorge Almeida. Information Systems, School of Industrial Engineering, Eindhoven University of Technology. e-mail: rjalmeida@tue.nl

## Friday, 20 November 2015

### Call for Papers WCCI 2016 Special Session: Computational intelligence techniques for the analysis of big and streaming data in complex systems

#### Aim:

Due to improved sensor technology, increasing storage space, and data availability, digital data sets are rapidly increasing with respect to size, dimensionality, and complexity. On the one hand, big and streaming data sets are becoming more and more popular in complex systems such as industrial manufacturing processes, surveillance, finance, social networks, or health-care. On the other hand, the dimensionality of data can easily reach a few thousand and data sources are often enriched by auxiliary information which gives crucial clues to avoid overfitting. These facts demand for advanced methods and tools which can cope with these big and complex data with respect to not only its sheer size, but also its often challenging statistical properties such as heterogeneous quality, data trends, presence of rare events, and necessity for strong regularisation. This special session will focus on advanced data analysis for big and streaming data which enable a reliable and computationally feasible access to such data sets.

#### Scope:

Submissions are encouraged according to the following non-exhaustive list of topics:
• Big data analytics
• Big data visualization
• Reliable machine learning for drift and trend
• Incremenental and lifelong learning
• Security and privacy in big data
• Regularization techniques for very high dimensional data
• Machine learning for heterogeneous and streaming data
• Constant memory algorithms for data analysis
• Analysis of sensor networks and social networks
• Distributed and multiple source machine learning techniques
• Big data applications e.g. in astronomy, health care, sensor networks
• Information and data fusion
• Semi-supervised learning
• Data correlation vs. information diversity
Submission by January 2016 at Congress website http://www.wcci2016.org/

#### Conference Proceedings:

This is a cross-disciplinary and CI applications Special Session, a submitted paper (if 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:

Prof.Barbara Hammer
CITEC centre of excellence
Bielefeld University
Germany
bhammer@techfak.uni-bielefeld.de

Prof.Frank Hsu
Department of Computer and Information Sciences
Fordham University, New York
USA
hsu@cis.fordham.edu

Prof.Marios M. Polycarpou
Department of Electrical and Computer Engineering
University of Cyprus, Nicosia
Cyprus

## Monday, 16 November 2015

### Call for Papers WCCI 2016 Special Session Computational Intelligence in Dynamics of Complex Networks: Models and Applications

Organized by Chung-Ming Ou and Chung-Ren Ou

Complex networks can be seen everywhere such as biology, chemistry, ecology, economics, physics, and even the Internet. There are many achievements in complex networks based on varied theories and models from mathematics and physics as well. However, the structures and internal properties of complex networks which lead to the major applications in sciences and technologies are still worth exploring. Among them, Computational Intelligence (CI) methodologies can be greatly contributed to solve these issues, in particular, the dynamics of complex networks. Applications of these CI methods to model and simulate complex networks are the main focus of this special session. The scope of the methodologies and ideas may include neural networks, artificial immune systems, swarm intelligence, fuzzy systems and other CI methods or general approaches from applied mathematics, physics, bio-inspired methodologies and control theory.

#### Scope and Topics

Topics of interest include but are not limited to:
• analysis and visualization of complex networks
• artificial immune systems
• big data and complex networks
• chaos in complex networks
• complex networks and self-organization
• control and dynamics of complex networks
• dynamics of complex networks
• mathematical modelling and analysis of complex networks
• modelling and simulation of biological networks
• robustness and stability of complex networks
• scale-free complex networks
• swarm intelligence and complex networks
• small-world complex network
• statistical properties of complex networks

## Friday, 6 November 2015

### Call for Papers WCCI 2016 Special Session: Spiking Neural Networks

Organisers: Nathan Scott & Nikola Kasabov (KEDRI, AUT)

Spiking Neural Networks are a rapidly emerging means of neural information processing, drawing inspiration from biological processes. There is presently considerable interest in this topic, especially with the recent announcement of large scale projects such as the “BRAIN Initiative” (US) and the “Human Brain Project” (EU). Due to their inspiration from human brain processes, SNN have the potential to advance technologies and techniques in fields as diverse as medicine, finance, computing, and indeed any field that involves complex spatio-temporal data. SNN can operate on noisy data, in changing environments at low power and with high effectiveness. We believe that this area is quickly establishing itself as an effective alternative to traditional machine learning technologies, and that interest in this area of research is growing rapidly. In this special session we intend to provide a platform for the discussion of contemporary areas of SNN, including theory, applications, and emerging technologies such as neuromorphic hardware.

#### Scope and Topics:

Topics of interest include, but are not limited to the following:
• Novel architectures
• SNN applications and case studies
• Learning algorithms for SNN, including Deep Learning
• Big data and stream data processing in SNN
• Theory or practice in biologically realistic neural simulation or biomimetic models
•  Neuromorphic hardware systems and applications
• Robotic applications of SNN
• Theory of SNN
• Optimisation of SNN
• Evolving SNN
• Any other topics relating to Spiking Neural Networks, their theory, or application.

See http://www.wcci2016.org for conference and submission details.
The paper submission deadline is the 15th of January, 2016

## Tuesday, 3 November 2015

### WCCI 2016 Workshops

IEEE WCCI 2016 is pleased to confirm the following workshops:
1. Computational Energy Management in Smart Grids - organized by Stefano Squartini, Derong Liu, Francesco Piazza, Dongbin Zhao and Haibo He.
2. Neuromorphic Computing and Cyborg Intelligence - organized by Huajin Tang, Gang Pan, Arindam Basu and Luping Shi

## Monday, 2 November 2015

### FIRST CALL FOR PAPERS

#### 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 simulatedautonomous 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

### IEEE Transactions on Neural Networks and Learning Systems: Volume 26, Issue 11, November 2015

1. Joint Learning of Multiple Sparse Matrix Gaussian Graphical Models
Authors: Feihu Huang; Songcan Chen
Page(s): 2606 - 2620

2. Mode-Dependent Stochastic Synchronization for Markovian Coupled Neural Networks With Time-Varying Mode-Delays
Authors: Huaguang Zhang; Junyi Wang; Zhanshan Wang; Hongjing Liang
Page(s): 2621 - 2634

3. A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition
Authors: Yong Zhang; Peng Li; Yingyezhe Jin; Yoonsuck Choe
Page(s): 2635 - 2649

4. Noise Level Estimation for Model Selection in Kernel PCA Denoising
Authors: Carolina Varon; Carlos Alzate; Johan A. K. Suykens
Page(s): 2650 - 2663

5. Active Learning-Based Pedagogical Rule Extraction
Authors: Enric Junque de Fortuny; David Martens
Page(s): 2664 - 2677

6. Impulsive Multiconsensus of Second-Order Multiagent Networks Using Sampled Position Data
Authors: Zhi-Hong Guan; Guang-Song Han; Juan Li; Ding-Xin He; Gang Feng
Page(s): 2678 - 2688

7. Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling
Authors: Sotirios P. Chatzis; Andreas S. Andreou
Page(s): 2689 - 2701

8. Universal Memcomputing Machines
Authors: Fabio Lorenzo Traversa; Massimiliano Di Ventra
Page(s): 2702 - 2715

9. Incremental Linear Discriminant Analysis: A Fast Algorithm and Comparisons
Authors: Delin Chu; Li-Zhi Liao; Michael Kwok-Po Ng; Xiaoyan Wang
Page(s): 2716 - 2735

10. An Information-Based Learning Approach to Dual Control
Authors: Tansu Alpcan; Iman Shames
Page(s): 2736 - 2748

11. Decentralized Output Feedback Adaptive NN Tracking Control for Time-Delay Stochastic Nonlinear Systems With Prescribed Performance
Authors: Changchun Hua; Liuliu Zhang; Xinping Guan
Page(s):
2749 - 2759

12. Robust Nonnegative Patch Alignment for Dimensionality Reduction
Authors: Xinge You; Weihua Ou; Chun Lung Philip Chen; Qiang Li; Ziqi Zhu; Yuanyan Tang
Page(s): 2760 - 2774

13. Adaptive Robust Output Feedback Control for a Marine Dynamic Positioning System Based on a High-Gain Observer
Authors: Jialu Du; Xin Hu; Hongbo Liu; C. L. Philip Chen
Page(s): 2775 - 2786

14. An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction
Authors: Ronay Ak; Valeria Vitelli; Enrico Zio
Page(s): 2787 - 2800

15. MRM-Lasso: A Sparse Multiview Feature Selection Method via Low-Rank Analysis
Authors: Wanqi Yang; Yang Gao; Yinghuan Shi; Longbing Cao
Page(s): 2801 - 2815

16. On the Universality of Axon P Systems
Authors: Xingyi Zhang; Linqiang Pan; Andrei Paun
Page(s): 2816 - 2829

17. Recurrent Neural Network for Computing the Drazin Inverse
Authors: Predrag S. Stanimirovic; Ivan S. Zivkovic; Yimin Wei
Page(s): 2830 - 2843

18. Adaptive Neural Network Dynamic Surface Control for a Class of Time-Delay Nonlinear Systems With Hysteresis Inputs and Dynamic Uncertainties
Authors: Xiuyu Zhang; Chun-Yi Su; Yan Lin; Lianwei Ma; Jianguo Wang
Page(s): 2844 - 2860

19. Improved Learning Performance of Hardware Self-Organizing Map Using a Novel Neighborhood Function
Authors: Hiroomi Hikawa; Yutaka Maeda
Page(s): 2861 - 2873

20. Robust Multitask Multiview Tracking in Videos
Authors: Xue Mei; Zhibin Hong; Danil Prokhorov; Dacheng Tao
Page(s): 2874 - 2890

21. A Projection Neural Network for Constrained Quadratic Minimax Optimization
Authors: Qingshan Liu; Jun Wang
Page(s): 2891 - 2900

22. Multistability and Instability of Neural Networks With Discontinuous Nonmonotonic Piecewise Linear Activation Functions
Authors: Xiaobing Nie; Wei Xing Zheng
Page(s): 2901 - 2913

23. Finite-Time Stabilizability and Instabilizability of Delayed Memristive Neural Networks With Nonlinear Discontinuous Controller
Authors: Leimin Wang; Yi Shen
Page(s): 2914 - 2924

24. Model-Free Primitive-Based Iterative Learning Control Approach to Trajectory Tracking of MIMO Systems With Experimental Validation
Page(s): 2925 - 2938

25. Enhanced Data-Driven Optimal Terminal ILC Using Current Iteration Control Knowledge
Authors: Ronghu Chi; Zhongsheng Hou; Shangtai Jin; Danwei Wang; Chiang-Ju Chien
Page(s): 2939 - 2948

26. Data-Driven H_\infty   Control for Nonlinear Distributed Parameter Systems
Authors: Biao Luo; Tingwen Huang; Huai-Ning Wu; Xiong Yang
Page(s): 2949 - 2961

27. Neurodynamics-Based Robust Pole Assignment for High-Order Descriptor Systems
Authors: Xinyi Le; Jun Wang
Page(s): 2962 - 2971

28. Sparse Density Estimation on the Multinomial Manifold
Authors: Xia Hong; Junbin Gao; Sheng Chen; Tanveer Zia
Page(s): 2972 - 2977

29. Spatiotemporal System Identification With Continuous Spatial Maps and Sparse Estimation
Authors: Parham Aram; Visakan Kadirkamanathan; Sean R. Anderson
Page(s): 2978 - 2983