A Framework for Evolutionary Computation in Agent-Based Systems
Robert E. Smith, Nicholas Kenelm Taylor · 1999
For agent-based systems to reach their full potential, an important capability for individual agents is adaptation. An adaptive technique that is particularly well suited to the agentbased paradigm is provided by evolutionary computation (EC). EC systems have been shown to develop complex groups of coevolved structures. In fact, Holland's original vision of artificial adaptive systems was more like an agentbased system than the typical centralized genetic algorithms (GAs) used today. Moreover, the EC techniques employed today are naturally distributable to an agent-based system. However, no standardized agent-based framework that includes EC capabilities is currently available. This paper introduces such a framework, based on Java, and IBM's Aglets. This framework provides a foundation for giving general agents EC capabilities. These capabilities are demonstrated in a basic optimization application, illustrating that the decentralized agents have emergent behavior which is equivalent to that of a centralized GA. The paper will also discuss the range of applications made possible by a standardized EC capability for agents.