Coevolution of heterogeneous multi-robot teams

Evolving multiple robots so that each robot acting independently can contribute to the maximization of a system level objective presents significant scientific challenges. For example, evolving multiple robots to maximize aggregate information in exploration domains (e.g., planetary exploration, search and rescue) requires coordination, which in turn requires the careful design of the evaluation functions. Additionally, where communication among robots is expensive (e.g., limited power or computation), the coordination must be achieved passively, without robots explicitly informing others of their states/intended actions. Coevolving robots in these situations is a potential solution to producing coordinated behavior, where the robots are coupled through their evaluation functions. In this work, we investigate coevolution in three types of domains: (i) where precisely

• Type: Conference
• Year: 2010
• Where: GECCO
• Authors: Matt Knudson, Kagan Tumer
• Keywords: Evaluation Function, GECCO 2010, Multiple Robots, Optimization, Robot