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.
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:
Dr. Robert G. Reynolds received his Ph.D. degree in Computer Science, specializing in Artificial Intelligence 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 complex organizations 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).