Deriving multi-agent coordination through filtering strategies
Eithan Ephrati, Martha E. Pollack, Sigalit Ur · 1995
We examine an approach to multi-agent coordination that builds on earlier work on enabling single agents to control their reasoning in dynamic environments. Specifically, we study a generalization of the filtering strategy. Where single-agent filtering means tending to bypass options that are incompatible with an agent's own goals, multi-agent filtering means tending to bypass options that are incompatible with other agents' known or presumed goals. We examine several versions of multi-agent filtering, which range from purely implicit to minimally explicit, and discuss the trade-offs among these. We also describe a series of experiments that demonstrate initial results about the feasibility of using multi-agent filtering to achieve coordination without explicit negotiation. 1 Introduction Distributed Artificial Intelligence (DAI) is concerned with effective interactions, and with the mechanisms by which these interactions can be achieved. Broadly speaking, two main approaches have be...