Fictitious play for finding system optimal routings in dynamic traffic networks
We introduce a novel procedure to compute system optimal routings in a dynamic traffic network. Fictitious play is utilized within a game of identical interests wherein vehicles are treated as players with the common payoff of average trip time experienced in the network. This decentralized approach via repeated play of the fictitious game is proven to converge to a local system optimal routing. Results from a large-scale computational test on a real network are presented.
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Volume (Year): 34 (2000)
Issue (Month): 2 (February)
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- Drew Fudenberg & David K. Levine, 1998.
"The Theory of Learning in Games,"
MIT Press Books,
The MIT Press,
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- Drew Fudenberg & David K. Levine, 1996. "The Theory of Learning in Games," Levine's Working Paper Archive 624, David K. Levine.
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- Monderer, Dov & Shapley, Lloyd S., 1996. "Fictitious Play Property for Games with Identical Interests," Journal of Economic Theory, Elsevier, vol. 68(1), pages 258-265, January. Full references (including those not matched with items on IDEAS)
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