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Task Force on Cultural Algorithms

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Aim

Cultural Algorithms are computational models of Cultural Evolution.  As such they provide a framework within which experiences of problem solvers embedded in a social fabric influence the collective knowledge of that group, its Culture. Culture is viewed as a network of passive and active knowledge sources. These knowledge sources are able integrate this knowledge, either individually or collectively, into their structure using data mining and machine learning tools. This updated Cultural Knowledge then is used to direct the modifications to individuals and their plans in the population space. Cultural Algorithms are an ideal framework for problems that require large amounts of domain knowledge to direct the collective decisions of individuals in the population. As such Cultural Algorithms have been successfully applied to problems in complex hierarchical systems characterized by large and extensive data sets (big data), many domain constraints, multiple objectives, and multiple agents within a large and spatially distributed social network. These applications include the evolution of urban centers, the rise and decline of ancient and modern social systems, engineering design and optimization, health care applications, game and robotic controller design, planning in manufacturing and industry, ecosystem evolution, and bioinformatics. 

Scope

This special session will focus on all aspects of Cultural Algorithms theory and application. Topics of interest may cover, but are not limited to the following:

·        Big Data and Analytics,

·        Social Intelligence in Networks,

·        Bio-informatics applications,

·        Multi-Cultural systems and subcultures,

·        Multi-Objective Optimization,

·        Many Objective  Optimization,

·        Multi-Agent Systems,

·        Ecosystem Modelling and Virtual World Applications,

·        Hybrid Systems Learning Systems,

·        Distributed Computing,

·        Social Intelligence in Games and Auctions,

·        Cloud Computing applications,

·        Constrained Optimization,

·        Real-World Applications,

·        Crowd Sourcing,

·        Hybrid agent populations: GA, GP, Neural, and Fuzzy agents.

·        Education. 

 

Key Resources

Recent activities and conferences:

-         Special Session on Cultural Algorithms, SSCI 2014, Orlando Florida, as part of the Swarm Intelligence Symposia.

-         Special Cultural Algorithms Track at 2014 IEEE World Congress on Computational Intelligence, Beijing, China, July 6-11, 2014.

-         Tutorial: “Theory and Applications of Cultural Algorithms”, 2014 World Congress on Computational Intelligence, July 6-11, Beijing, China, 2014.

-         “Cultural Algorithms and Applications”, Keynote Talk, 2014 Annual Artificial Intelligence Summit, Philadelphia, PA, August 27-29, 2014.

-         Invited Tutorial: “The Design of Controllers for Robots and Softbots Using Cultural Algorithms”, 2nd Annual IEEE Conference on Robotic Intelligence and Technological Applications”, December 18-20, 2013, Denver, Colorado.

-         Special Session on Cultural Algorithms, IEEE CEC 2013, Can Cu, Mexico, Jun 17-20, 2014.

-         “Tutorial: Cultural Algorithms: Embedding Social Intelligence into Reality Games”, IEEE World Congress on Computational Intelligence, June 7-12, 2012, Brisbane, Austrailia.

-         Special Cultural Algorithms Track at 2012 IEEE World Congress on Computational Intelligence, Brisbane, Austrailia.

-         “Tutorial: Cultural Algorithms: Embedding Social Intelligence into Reality Games”, IEEE World Congress on Computational Intelligence, June 7-12, 2012, Brisbane, Austrailia.

-         Special Cultural Algorithms Track at 2012 IEEE World Congress on Computational Intelligence, Brisbane, Austrailia.

-         “Tutorial: Cultural Algorithms: Computational Intelligence in Reality Games”, IEEE Conference on Computational Intelligence in Games, Seoul, Korea, August 30, 2011.

-         “Tutorial: Cultural Algorithms: Harnessing the Power of Social Intelligence: the Land Bridge Reality Game”, IEEE Spring Symposia on Computational Intelligence, Paris,  France, April 11-14, 2011.

Recent Journal Publications:

-         Reynolds, R.G, Vitale, K., Che, X., O’Shea, J. and Salaymeh,A.Using Virtual Worlds to Facilitate the Exploration Of Ancient LandscapesInternational Journal of Swarm Intelligence Research (IJSIR), Volume 4, No. 2, pp: 49-83, 2013

-         Reynolds, R.G., Kinniard-Heether, “Optimization  Problem Solving with Auctions in Cultural Algorithms”, in International Journal of Memetics, 2013.

-         Kohler, T., Gummerman, G., and Reynolds, R.G., “Exodus on Computers”, in Spektrum (German Scientific American), Jan. 2013, pp: 88-93.

-         O’Shea, J., Lemke, A., and Reynolds, R.G., “Nobody Knows the Ways of the Caribou”, in Quaternary International, January 12, 2013, Elsevier Press.

-         Ali, M., Salhieh, A., and Snanieh, Randa T. Abu., and Reynolds, R.G.,Boosting Cultural Algorithms with a Heterogeneous Layered Social Fabric Influence Function”, in Journal of Computational and Mathematical  Organization Theory, Kluwer Academic Publishers, 2012.

-         Vitale, K., Reynolds, R. G., O’Shea, J., and Meadows, G., Exploring Ancient Landscapes Under Lake Huron Using Cultural Algorithms, in Procedia Computer Sciences, Elsevier Press, Volume 6, pp: 303-310, 2011.

-         Reynolds, R.G., Che, X., and Ali, M., “Weaving the Social Fabric: The Past, Present and Future of Optimization Problem Solving with Culture Algorithms, International Journal of Complexity and Cybernetics, 2011.

-         Snaineh R., Younes A., Ali, M., Salhieh A., and Reynolds, R. G., “I-Architect” A Virtual Reality CAD System”,  IEEE Multi-Disciplinary Engineering Education Magazine,  Vol. 6, No. 4, pp:14-21, 2011.

-         Reynolds, R.G., Kobti, Z., Kohler, T., and Yap, L., “Unraveling Ancient Mysteries: Re-imagining the Past Using Evolutionary Computation in a Computer Gaming Environment”, IEEE Transactions on Evolutionary Computation, Vol. 9, No. 6, pp: 708-720, December, 2005.

-         Kohler, T., Gummerman, G., and Reynolds, R. G., “Virtual Archaeology”, Scientific American, vol. 293, no. 1, pp: 76-84, July, 2005.

 

Task Force Chair

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Robert G. Reynolds

robert.reynolds@wayne.edu

Department of Computer Science

Wayne State University, USA

 

Dr. Robert G. Reynolds received his Ph.D. degree in Computer Science, specializing in Artificial Intelligence,   in 1979 from the University of Michigan, Ann Arbor. He is currently a professor of Computer Science and director of the Artificial Intelligence Laboratory at Wayne State University. He is an Adjunct Associate Research Scientist with the Museum of Anthropology at the University of Michigan-Ann Arbor, a member of the Complex Systems Group at the University of Michigan-Ann Arbor, and is a participant in the University of Michigan –Wayne State University NSF IGERT program on Incentive-Based Design. His interests are in the development of computational models of cultural evolution for use in the simulation of virtual worlds and in computer gaming applications. Dr. Reynolds produced a framework, Cultural Algorithms, in which to express and computationally test various theories of social evolution using multi-agent simulation models. He has applied these techniques to problems concerning the origins of the state in the Valley of Oaxaca, Mexico, the emergence of prehistoric urban centers, the origins of language and culture, and the disappearance of the Ancient Anazazi in Southwestern Colorado using game programming techniques. He has co-authored three books; Flocks of the Wamani (1989, Academic Press), with Joyce Marcus and Kent V. Flannery; The Acquisition of Software Engineering Knowledge (2003, Academic Press), with George Cowan; and Excavations at San Jose Mogote 1: The Household Archaeology with Kent Flannery and Joyce Marcus (2005, Museum of Anthropology-University of Michigan Press).

 

Task Force Vice-Chairs in alphabetical order (to be confirmed)

 

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Mostafa Z. Ali

mzali.pn@gmail.com

Department of Computer Information Systems

Jordan University of Science & Technology, Jordan

 

Mostafa Z. Ali, received the Bachelor degree in Applied Mathematics at Jordan University of Science &Technology (JUST)., Irbid, Jordan, in 2000. He finished his Masters in Computer Science at the University of Michigan-Dearborn, Michigan, USA in 2003. He finished his Ph.D. in computer science/Artificial Intelligence at Wayne State University, Michigan, USA in 2008. Ali is a professor of computer information systems at Jordan University of Science & Technology, Irbid, Jordan. His research interests include artificial intelligence, evolutionary computation, Cultural Algorithms, Virtual Reality, data mining, Bioinformatics Databases, Computer Graphics, and image processing. He is a member of the IEEE, the IEEE computer society, and the ACM.

 

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Carlos Coello Coello

ccoello@cs.cinvestav.mx

Depto. de Computación

CINVESTAV-IPN

 

Carlos Coello Coello received his Ph.D. degree in Civil Engineering in 1991 from the Universidad Autonoma de Chiapas.  He received his M.S. in Computer Science from Tulane University in 1993. He received his Ph.D. in Computer Science in 1996 in the area of multi-objective optimization. His current topics of research include multi-objective optimization using meta-heuristics, and
bio-inspired meta-heuristics for optimization. These include evolutionary algorithms, artificial immune systems, particle swarm optimization, and cultural algorithms
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Ziad Kobti

kobti@uwindsor.ca

School of Computer Science

University of Windsor, Canada

 

 

 

Yuhui Shi

yuhui.shi@xjtlu.edu.cn

Dept. of Electrical and Electronic Engineering

XI'an Jiaotong-Liverpool University

 

Yuhui Shi received the Ph.D. degree in electronic engineering from Southeast University, Nanjing, China, in 1992. He is currently a Professor with the Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China. His current research interests include computational intelligence techniques (including swarm intelligence) and their applications.
Dr. Shi is the Editor-in-Chief of the International Journal of Swarm Intelligence Research and an Associate Editor of the IEEE Transactions on Evolutionary Computation.

 

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P. N. Suganthan

epnsugan@ntu.edu.sg

School of Electrical & Electronic Engineering

Nanyang Technological University, Singapore

 

 

 

 

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Gary Yen

gyen@okstate.edu

School of Electrical and Computer Engineering

Oklahoma State University

 

Gary Yen received his Ph.D. degree in electrical and computer engineering from the University of Notre Dame in 1992. He is currently a Professor in the School of Electrical and Computer Engineering, Oklahoma State University (OSU). Before joined OSU in 1997, he was with the Structure Control Division, U.S. Air Force Research Laboratory in Albuquerque, New Mexico. His research is supported by the DoD, DoE, EPA, NASA, NSF, and Process Industry. His research interest includes intelligent control, computational intelligence, conditional health monitoring, signal processing and their industrial/defense applications. He is an IEEE Fellow. Dr. Yen was an associate editor of the IEEE Control Systems Magazine, IEEE Transactions on Control Systems Technology, Automatica, Mechantronics, IEEE Transactions on Systems, Man and Cybernetics, Part A and Part B and IEEE Transactions on Neural Networks. He is currently serving as an associate editor for the IEEE Transactions on Evolutionary Computation and International Journal of Swarm Intelligence Research. He served as the General Chair for the 2003 IEEE International Symposium on Intelligent Control held in Houston, Texas and 2006 IEEE World Congress on Computational Intelligence held in Vancouver, Canada. Dr. Yen served as President of the IEEE Computational intelligence Society 2010-2011 and is the founding editor-in-chief of the IEEE Computational Intelligence Magazine 2006-2009. He is an IEEE Fellow.

 

                               

Task Force Members in alphabetical order (to be confirmed)

 

 

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Dan Ashlock

dashlock@uoguelph.ca

 

 

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Ratna Babu Chinnam

r_chinnam@wayne.edu

 

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Rami Gharaibeh

rami@just.edu.jo



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Sean Che

sean_che@wayne.edu

 

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Tzung-Pei Hong

tphong@nuk.edu.tw

 

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Thaer W. Jayyousi

al6854@wayne.edu

Department of Computer Science

Wayne State University, U.S.A

 

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Yaochu Jin

Yaochu.Jin@surrey.ac.uk

 

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Jong-Hwan Kim

johkim@rit.kaist.ac.kr

 

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Dapeng Liu

dliu@wayne.edu

 

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Mohammad R. Raeesi

raeesim@uwindsor.ca

School of Computer Science

University of Windsor, Canada

 

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Nestor Rychtyckyj

nrychtyc@ford.com

 

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Ayad Salhieh

a.salhieh@ack.edu.kw

 

 

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KC Tan

eletankc@nus.edu.sg

 

 

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Jun Zhang

junzhanghk@gmail.com

 

 

 

 

 

 

 

 

 

 

 

 

 

 

                                                                                               

 

WEB Designer: Areej Jameel Salaymeh eg6674@wayne.edu  @2014