# ECAI-2000 Conference Paper

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.

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.