Comments (2)
In summary, multiagent learning is definitely a good tie between game theory and AI: there is much work that falls in the intersection of these two areas, and the article by Shoham, Powers, and Grenager very effectively characterizes both its strengths and current limitations. But from an AI perspective, multiagent learning should be considered more broadly than game theory can address. In this context, how (and perhaps whether) multiagent learning can be usefully applied in complex domains is still a large open question.
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Really clear minded and complementing Shoham et al's list of ideas #11!
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