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.
Authors are invited to submit their original and unpublished work in the following areas:
Please forward your proposals with detailed abstract and bio-sketches of the speakers to Symposium Co-Chairs and SSCI Keynote-Tutorial Chair, Dr S Das.
Please forward your special session proposals to Symposium Co-Chairs.
Dr. Zexuan Zhu
College of Computer Science and Software Engineering, Shenzhen
University, China
E-mail: zhuzx@szu.edu.cn
Dr. Maoguo Gong
Institute of Intelligent Information Processing, Xidian University,
China
E-Mail: gong@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@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@ntu.edu.sg
Homepage:
http://www.ntu.edu.sg/home/asysong/
Prof. Pablo Moscato, The University of Newcastle, Australia
Prof. Hisao Ishibuchi, Osaka Prefecture University, Japan
Prof. Qingfu Zhang, University of Essex, UK
Prof. Licheng Jiao, Xidian University, China
Dr. Jim Smith, University of the West of England
Dr. Natalio Krasnogor, University of Nottingham, United Kingdom
Dr. Goh, Chi Keong, Advanced Technology Centre, Rolls-Royce
Singapore Pte Ltd, Singapore
Dr. Swagatam Das, Jadavpur University, India
Dr. Steven Gustafson, GE Global Research, USA
Dr. Chuan-Kang Ting, National Chung Cheng University, Taiwan
Dr. Ferrante Neri, University of Jyväskylä, Finland
Dr. Shaheen Fatima, Loughborough University, United Kingdom
Dr. Ke Tang, University of Science and Technology of China, China
Dr. Yong Wang, Central South University of China, China
Dr. Kai Qin, School of Automation, Southeast University, China
Dr. Bin Li, University of Science and Technology of China, China