Title: Modeling the Evolution of Cooperation
Dr. Thomas Shultz, McGill University
Date: April 8, 2011
Time: 10:20 am
Room: 1279 Anthony Hall
An important explanation of cooperation is that it is favored by natural selection, as long as cooperation is ethnocentrically focused on one’s own genetic kind. This talk presents new computer simulations that further explore the limits and underlying principles of this phenomenon. Ethnocentrism out-competes its closest competitor by directly exploiting the universal cooperation offered by humanitarianism. Selfish and traitorous strategies are self-limited by their lack of cooperation with their own kind. Ethnocentric cooperation is driven by local child-placement and maintained by identifiable group tags. In symmetric non-zero-sum games, ethnocentrism prevails whenever the temptation to defect exceeds the penalty for unreciprocated cooperation – otherwise there is humanitarian dominance. Hamilton’s rule about favoring kin is qualified by noting that cooperation is not symmetrical, but instead favors the young, even if age is just a tag. When aging is more realistically implemented, life-history traits co-evolve as in natural species. Humanitarianism can prevail if the extra cognitive cost of comparing tags in ethnocentrism is considered, although with a slight, but significant, decrease in cooperative behaviors. Cooperative inter-group mating favors humanitarianism and cooperation, regardless of how offspring are labeled. More generally, simulation experiments continue to uncover principles by which complex phenomena emerge from simple processes.
Thomas Shultz (PhD Yale, Psychology) is Professor of Psychology and Associate Member of the School of Computer Science at McGill University. He teaches courses in Computational Psychology and Cognitive Science. He is a Fellow of the Canadian Psychological Association, and a founder and former Coordinator of McGill Cognitive Science. Research interests include connectionism, cognitive science, cognitive development, relations between knowledge and learning, and more recently evolution. He has over 200 research publications in these areas. He is a Member of the IEEE Neural Networks Society Autonomous Mental Development Technical Committee and Chair of the AMD Task Force on Developmental Psychology.