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A formal framework is presented that models communication and promises in multi-agent interactions. This framework generalizes previous work on cooperation without communication, and shows the ability of communication to resolve conflicts among agents having disparate goals. Using a deal-making mechanism, agents are able to coordinate and cooperate more easily than in the communication-free model. In addition, there are certain types of interactions where communication makes possible mutually beneficial activity that is otherwise impossible to coordinate. Additional keywords: artificial intelligence; game theory; theorems; mathematical models. (Author).

Abstract: "Research in Distributed Artificial Intelligence has historically focused on two distinct classes of problems. One paradigm, 'planning for multiple agents, ' considers issues inherent in centrally directed multiple-agent execution (Smith's Contract Net [15,14] falls into this category, as does other DAI work such as [11,10]). In the second paradigm, 'distributed planning, ' multiple agents participate more autonomously in deciding upon and coordinating their own actions [2,12,3].

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The probabilistic extension is obtained by a representation of interactions that explicitly incorporates uncertainty about other players' moves. A three-level hierarchy of rationality is defined, corresponding to ordinal, stochastic, and utility dominance among alternative outcomes. The previous deduction-based formalism is recast in probabilistic terms, and is seen to be a particular special case of a more encompassing dominance theory. A technique is presented for using ordinal, stochastic, and utility dominance in interactions with other agents operating various axioms of rationality."