MC 2011 - MC 2011 2011 IEEE Workshop on Memetic Computing
Topics/Call fo Papers
MC 2011
2011 IEEE Workshop on Memetic Computing
Memetic computation (MC) represents one of the recent growing areas in computational intelligence. Inspired by Darwinian principles of natural evolution and Dawkins notion of a meme, the term “Memetic Algorithm” (MA) is generally viewed as being close to a form of population-based hybrid global evolutionary algorithm (EA) coupled with a learning procedure capable of local refinements. In diverse contexts, MAs are also commonly known as hybrid EAs, Baldwinian EAs, Lamarckian EAs, cultural algorithms and genetic local search. The rapidly growing research interest in MA is demonstrated by the significant increase in the number of research publications on MA.
MC offers a broader scope that captures appropriately the essence of existing and potential work in the field. It is defined as a paradigm that uses the notion of meme(s) as units of information encoded in computational representations for the purpose of problem-solving. Besides MA, Representations in the forms such as decision tree, artificial neural works, fuzzy system, graphs, etc., are examples of various manifestations of memes encoding. Taking a lead from the multi-faceted definitions and roles of the term "meme" in memetics, a plethora of potentially rich MC methodologies, frameworks and operational meme-inspired algorithms have been developed with considerable success in several real-world domains in the last two decades.
Despite the vast research on MC, there remain many open issues and opportunities that are continually emerging as intriguing challenges for the field. The expanse of MC remains largely untapped and judging from the research activities devoted to this area in the last few years, it is a matter of time before we see more demonstrative and ground-breaking applications in this rich research arena. The aim of this symposium is to reflect the latest advances in MC, to explore the emerging or future directions of memetic research in computational intelligence, and to raise the awareness of the computing community at large on this effective technology. Specifically, we endeavor to demonstrate the current state-of-the-art concepts, theory, and practice of MC.
Topics
Authors are invited to submit their original and unpublished work in the following areas:
Novel competitive, collaborative and cooperative frameworks of memetic computation,
Analytical and/or theoretical studies that enhance our understanding on the behaviors of memetic computation,
Formal and Probabilistic Single/Multi-Objective memetic frameworks,
Cognitive, Brain, individual learning, and social learning inspired memetic computation
Partial or full or meta-Lamarckian/Baldwinian, meta-learning, agent based memetic computation.
Memetic frameworks using surrogate or approximation methods,
Memetic frameworks for computationally expensive problems and real-world applications,
Knowledge incorporation in memetic computation
Symposium Co-Chairs
Dr. Zexuan Zhu
College of Computer Science and Software Engineering, Shenzhen University, China
E-mail: zhuzx-AT-szu.edu.cn
Dr. Maoguo Gong
Institute of Intelligent Information Processing, Xidian University, China
E-Mail: gong-AT-ieee.org
Homepage: http://see.xidian.edu.cn/faculty/mggong/index.htm
Dr. Zhen Ji
College of Computer Science and Software Engineering, Shenzhen University, China
E-mail: jizhen-AT-szu.edu.cn
Homepage: http://csse.szu.edu.cn/Staffs/jiZhen.shtml
Dr. Yew-Soon Ong
School of Computer Engineering, Nanyang Technological University, Singapore
E-mail: asysong-AT-ntu.edu.sg
Homepage: http://www.ntu.edu.sg/home/asysong/
Program Committee
(tentative)
Dr. Swagatam Das, Department of Electronics and Telecommunication Engineering, Jadavpur University
Prof. Donald C. Wunsch, M.K. Finley Missouri Distinguished Professor, Electrical & Computer Engineering, University of Missouri Rolla, USA
Dr. Meng-Hiot Lim, Electrical & Electronics Engineering, Nanyang Technological University, Singapore
Prof. Licheng Jiao, Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, China
Dr. Natalio Krasnogor, University of Nottingham, United Kingdom
Dr. Steven Gustafson, GE Global Research, USA
Dr. Kay Chen Tan, National University of Singapore, Singapore
Dr. Yaochu Jin, Honda Research Institute Europe, Germany
Dr. Chuan-Kang Ting, National Chung Cheng University, Taiwan
Dr. Ferrante Neri, University of Jyväskylä, Finland
Dr. Jim Smith, University of the West of England
Dr. Ruhul Sarker, The University of New South Wales
Dr. Shaheen Fatima, Loughborough University, United Kingdom
Dr. Goh, Chi Keong, Advanced Technology Centre, Rolls-Royce Singapore Pte Ltd, Singapore
Dr. Lee Kee Khoon, Gary, Institute of High Performance Computing, A-Star, Singapore
Dr. Yanqing Zhang, Department of Computer Science, Georgia State University, Atlanta, Georgia, USA
Dr. Pablo Moscato, School of Electrical Engineering and Computer Science The University of Newcastle, Australia
Dr. Carlos Cotta, Universidad de Málaga, ETSI Informática, Campus de Teatinos, Spain
Dr. Ke Tang, School of Computer Science and Technology, University of Science and Technology of China, China
Prof. Jun Zhang, Department of Computer Science, Sun Yat-Sen University, China
Prof. Qingfu Zhang, (University of Essex, UK)
Prof. Yuhui Shi, (Xi'an Jiaotong-Liverpool University, China)
Dr. Aimin Zhou, (Eastern China Normal University)
Dr. Yong Wang, (Central South University of China)
Dr. Ying Tan, (Peking University, China)
Dr. Haibin Duan, (Beihang University, China)
2011 IEEE Workshop on Memetic Computing
Memetic computation (MC) represents one of the recent growing areas in computational intelligence. Inspired by Darwinian principles of natural evolution and Dawkins notion of a meme, the term “Memetic Algorithm” (MA) is generally viewed as being close to a form of population-based hybrid global evolutionary algorithm (EA) coupled with a learning procedure capable of local refinements. In diverse contexts, MAs are also commonly known as hybrid EAs, Baldwinian EAs, Lamarckian EAs, cultural algorithms and genetic local search. The rapidly growing research interest in MA is demonstrated by the significant increase in the number of research publications on MA.
MC offers a broader scope that captures appropriately the essence of existing and potential work in the field. It is defined as a paradigm that uses the notion of meme(s) as units of information encoded in computational representations for the purpose of problem-solving. Besides MA, Representations in the forms such as decision tree, artificial neural works, fuzzy system, graphs, etc., are examples of various manifestations of memes encoding. Taking a lead from the multi-faceted definitions and roles of the term "meme" in memetics, a plethora of potentially rich MC methodologies, frameworks and operational meme-inspired algorithms have been developed with considerable success in several real-world domains in the last two decades.
Despite the vast research on MC, there remain many open issues and opportunities that are continually emerging as intriguing challenges for the field. The expanse of MC remains largely untapped and judging from the research activities devoted to this area in the last few years, it is a matter of time before we see more demonstrative and ground-breaking applications in this rich research arena. The aim of this symposium is to reflect the latest advances in MC, to explore the emerging or future directions of memetic research in computational intelligence, and to raise the awareness of the computing community at large on this effective technology. Specifically, we endeavor to demonstrate the current state-of-the-art concepts, theory, and practice of MC.
Topics
Authors are invited to submit their original and unpublished work in the following areas:
Novel competitive, collaborative and cooperative frameworks of memetic computation,
Analytical and/or theoretical studies that enhance our understanding on the behaviors of memetic computation,
Formal and Probabilistic Single/Multi-Objective memetic frameworks,
Cognitive, Brain, individual learning, and social learning inspired memetic computation
Partial or full or meta-Lamarckian/Baldwinian, meta-learning, agent based memetic computation.
Memetic frameworks using surrogate or approximation methods,
Memetic frameworks for computationally expensive problems and real-world applications,
Knowledge incorporation in memetic computation
Symposium Co-Chairs
Dr. Zexuan Zhu
College of Computer Science and Software Engineering, Shenzhen University, China
E-mail: zhuzx-AT-szu.edu.cn
Dr. Maoguo Gong
Institute of Intelligent Information Processing, Xidian University, China
E-Mail: gong-AT-ieee.org
Homepage: http://see.xidian.edu.cn/faculty/mggong/index.htm
Dr. Zhen Ji
College of Computer Science and Software Engineering, Shenzhen University, China
E-mail: jizhen-AT-szu.edu.cn
Homepage: http://csse.szu.edu.cn/Staffs/jiZhen.shtml
Dr. Yew-Soon Ong
School of Computer Engineering, Nanyang Technological University, Singapore
E-mail: asysong-AT-ntu.edu.sg
Homepage: http://www.ntu.edu.sg/home/asysong/
Program Committee
(tentative)
Dr. Swagatam Das, Department of Electronics and Telecommunication Engineering, Jadavpur University
Prof. Donald C. Wunsch, M.K. Finley Missouri Distinguished Professor, Electrical & Computer Engineering, University of Missouri Rolla, USA
Dr. Meng-Hiot Lim, Electrical & Electronics Engineering, Nanyang Technological University, Singapore
Prof. Licheng Jiao, Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, China
Dr. Natalio Krasnogor, University of Nottingham, United Kingdom
Dr. Steven Gustafson, GE Global Research, USA
Dr. Kay Chen Tan, National University of Singapore, Singapore
Dr. Yaochu Jin, Honda Research Institute Europe, Germany
Dr. Chuan-Kang Ting, National Chung Cheng University, Taiwan
Dr. Ferrante Neri, University of Jyväskylä, Finland
Dr. Jim Smith, University of the West of England
Dr. Ruhul Sarker, The University of New South Wales
Dr. Shaheen Fatima, Loughborough University, United Kingdom
Dr. Goh, Chi Keong, Advanced Technology Centre, Rolls-Royce Singapore Pte Ltd, Singapore
Dr. Lee Kee Khoon, Gary, Institute of High Performance Computing, A-Star, Singapore
Dr. Yanqing Zhang, Department of Computer Science, Georgia State University, Atlanta, Georgia, USA
Dr. Pablo Moscato, School of Electrical Engineering and Computer Science The University of Newcastle, Australia
Dr. Carlos Cotta, Universidad de Málaga, ETSI Informática, Campus de Teatinos, Spain
Dr. Ke Tang, School of Computer Science and Technology, University of Science and Technology of China, China
Prof. Jun Zhang, Department of Computer Science, Sun Yat-Sen University, China
Prof. Qingfu Zhang, (University of Essex, UK)
Prof. Yuhui Shi, (Xi'an Jiaotong-Liverpool University, China)
Dr. Aimin Zhou, (Eastern China Normal University)
Dr. Yong Wang, (Central South University of China)
Dr. Ying Tan, (Peking University, China)
Dr. Haibin Duan, (Beihang University, China)
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Last modified: 2010-11-01 03:49:30