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Multiagent learning is not the answer. It is the question.
Peter Stone.
Artificial
Intelligence, 171:402–05, May 2007.
Response to Shoham, Powers, and Grenager If Multi-Agent Systems is
the Answer, What is the Question?, available from Shoham's webpage.
Official version from the AIJ
publisher's webpage.
[PDF]117.9kB [postscript]91.0kB
The article by Shoham, Powers, and Grenager called ``If multi-agent learning is the answer, what is the question?'' does a great job of laying out the current state of the art and open issues at the intersection of game theory and artificial intelligence (AI). However, from the AI perspective, the term ``multiagent learning'' applies more broadly than can be usefully framed in game theoretic terms. In this larger context, how (and perhaps whether) multiagent learning can be usefully applied in complex domains is still a large open question.
@Article{AIJ07, Author="Peter Stone", title="Multiagent learning is not the answer. It is the question", journal="Artificial Intelligence", month="May", year="2007", volume="171",issue="7",pages="402--05", abstract=" The article by Shoham, Powers, and Grenager called ``If multi-agent learning is the answer, what is the question?'' does a great job of laying out the current state of the art and open issues at the intersection of game theory and artificial intelligence (AI). However, from the AI perspective, the term ``multiagent learning'' applies more broadly than can be usefully framed in game theoretic terms. In this larger context, how (and perhaps whether) multiagent learning can be usefully applied in complex domains is still a large open question. ", wwwnote={Response to Shoham, Powers, and Grenager <b>If Multi-Agent Systems is the Answer, What is the Question?</b>, available from <a href="http://ai.stanford.edu/~shoham/">Shoham's webpage</a>.<br> <a href="http://dx.doi.org/10.1016/j.artint.2006.12.005">Official version from the <a href="http://www.elsevier.com/locate/artint">AIJ</a> publisher's webpage.}, }
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