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Stochastic Learning of Strategic Equilibria for Auctions (1999)  (Make Corrections)  
Samy Bengio, Yoshua Bengio
Neural Computation



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Abstract: This paper presents a new application of stochastic adaptive learning algorithms to the computation of strategic equilibria in auctions. The proposed approach addresses the problems of tracking a moving target and balancing exploration (of action space) versus exploitation (of better modeled regions of action space). Neural networks are used to represent a stochastic decision model for each bidder. Experiments confirm the correctness and usefulness of the approach. (Update)

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BibTeX entry:   (Update)

@article{ bengio99stochastic,
    author = "Samy Bengio and Yoshua Bengio and Jacques Robert and Gilles Belanger",
    title = "Stochastic Learning of Strategic Equilibria for Auctions",
    journal = "Neural Computation",
    volume = "11",
    number = "5",
    pages = "1199-1209",
    year = "1999",
    url = "citeseer.ist.psu.edu/bengio99stochastic.html" }
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