Revised Papers from the International Workshop on Infrastructure for Multi-Agent Systems: Infrastructure for Agents, Multi-Agent Systems, and Scalable Multi-Agent Systems
An approach to analyzing the need for meta-level communication
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
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There are many formal approaches to specifying how the mental state of an agent entails that it perform particular actions. These approaches put the agent at the center of analysis. For some questions and purposes, it is more realistic and convenient for the center of analysis to be the task environment, domain, or society of which agents will be a part. This paper presents such a task environment-oriented modeling framework that can work hand-in-hand with more agent-centered approaches. Our approach features careful attention to the quantitative computational interrelationships between tasks, to what information is available (and when) to update an agent''s mental state, and to the general structure of the task environment rather than single-instance examples. This framework avoids the methodological problems of relying solely on single-instance examples, and provides concrete, meaningful characterizations with which to state general theories. Task environment models built in our framework can be used for both analysis and simulation to answer questions about how agents should be organized, or the effect of various coordination algorithms on agent behavior. This paper is organized around an example model of cooperative problem solving in a distributed sensor network.