Unifying learning in games and graphical models

Conference item

The ever increasing use of intelligent multi-agent systems poses increasing demands upon them. One of these is the ability to reason consistently under uncertainty. This, in turn, is the dominant characteristic of probabilistic learning in graphical models which, however, lack a natural decentralised formulation. The ideal would, therefore, be a unifying framework which is able to combine the strengths of both multi-agent and probabilistic inference In this paper we present a unified interpre...

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Authors: Rezek, I; Roberts, S; Rogers, A; Dash, R; Jennings, N

• Publication status: Published
• Host title: 2005 7TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), VOLS 1 AND 2
• Volume: 2
• Pages: 1193-1198
• Publication date: 2005-01-01
• DOI: 10.1109/ICIF.2005.1591992
• ISBN: 0780392868