TY - GEN
T1 - Iterated regret minimization
T2 - 21st International Joint Conference on Artificial Intelligence, IJCAI 2009
AU - Halpern, Joseph Y.
AU - Pass, Rafael
PY - 2009
Y1 - 2009
N2 - For some well-known games, such as the Traveler's Dilemma or the Centipede Game, traditional game-theoretic solution concepts - most notably Nash equilibrium - predict outcomes that are not consistent with empirical observations. We introduce a new solution concept, iterated regret minimization, which exhibits the same qualitative behavior as that observed in experiments in many games of interest, including Traveler's Dilemma, the Centipede Game, Nash bargaining, and Bertrand competition. As the name suggests, iterated regret minimization involves the iterated deletion of strategies that do not minimize regret.
AB - For some well-known games, such as the Traveler's Dilemma or the Centipede Game, traditional game-theoretic solution concepts - most notably Nash equilibrium - predict outcomes that are not consistent with empirical observations. We introduce a new solution concept, iterated regret minimization, which exhibits the same qualitative behavior as that observed in experiments in many games of interest, including Traveler's Dilemma, the Centipede Game, Nash bargaining, and Bertrand competition. As the name suggests, iterated regret minimization involves the iterated deletion of strategies that do not minimize regret.
UR - http://www.scopus.com/inward/record.url?scp=77954091074&partnerID=8YFLogxK
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AN - SCOPUS:77954091074
SN - 9781577354260
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 153
EP - 158
BT - IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence
PB - International Joint Conferences on Artificial Intelligence
Y2 - 11 July 2009 through 16 July 2009
ER -