Efficient Evaluation Functions for Evolving Coordination

Abstract-- This paper presents a method for creating evaluation functions that efficiently promote coordination in a multiagent system, allowing single-agent evolutionary computation techniques to be extended to multi-agent domains. While this problem can be addressed directly by treating the entire multiagent system as a large single agent, the search space is prohibitively large in most cases. Instead, the proposed method focuses on having each agent use its own evolutionary computation method to maximize its own evaluation function. There are two fundamental issue in this approach: 1) how to create an evaluation function for an agent that is aligned with the global evaluation function and 2) how to create an evaluation function that is sensitive to the fitness changes of the agent, while relatively insensitive to the fitness changes of other agents. If the first issue is not addressed, the evolved agents will not coordinate well. If the second issue is not addressed, the collective ...

• Type: Journal
• Year: 2008
• Where: EC
• Authors: Adrian K. Agogino, Kagan Tumer
• Keywords: EC 2008, ECommerce, Evaluation Functions, Evolutionary Computation, Global Evaluation