TOWARD A TAXONOMY OF MULTIAGENT SYSTEMS

As intelligent systems become more pervasive and capture more expert and organizational knowledge, the expectation that they be integrated into larger problem-solving systems is heightened. To capitalize on these investments and more fully exploit their potential as knowledge repositories, general principles for their integration must be developed. Although simulated and prototype systems described in the literature provide solutions to some practical problems, most are empirical (or often simply intuitive) in design, emerging from implementation strategy instead of general principles. As a step toward the development of such principles, this paper presents a taxonomy for multi-agent systems that defines alternative architectures based on fundamental distributed, intelligent system characteristics. © 1993 Academic Press. All rights reserved.