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Team-Solvability: A Model-Theoretic Perspective

Alessandro Agostini

At present, the extension of {\em formal learning theory} to the multi-agent case considers ``teams'' of agents sharing a common end. Success is achieved if one or more of the agents is successful, and cooperation is not involved in the team formation. Unfortunately, this is rarely the idea of ``successful team'' we have in mind. One generally expects agents' behaviour to influence each other in a way that is not captured by the present paradigms. A real problem in extending single agent learning methods to multi-agent setting is thus determining {\em paradigms of cooperation}. This paper makes a contribution to the solution of this problem. First, we advance a paradigm of cooperation as a kind of two-person repeated game and compare it to a major paradigm of solvability for isolated agents. Second, we pay attention to a subset of {\em unsuccessful} agents who take advantage from teamwork. For these agents, cooperation is proved to be a key of success. The formal results are raised within the model-theoretic tradition of formal learning theory.

Keywords: discovery, inductive logic, multi-agent systems

Citation: Alessandro Agostini: Team-Solvability: A Model-Theoretic Perspective. In W.Horn (ed.): ECAI2000, Proceedings of the 14th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2000, pp.333-337.

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ECAI-2000 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Humboldt University on behalf of Gesellschaft für Informatik.