Rational Multi-Agent Search
We study games in which players search for an optimal action profile. All action profiles are either a success, with a payoff of one, or a failure, with a payoff of zero. Players do not know the location of success profiles; instead each player is privately informed about the marginal distribution of success profiles over his actions. We characterize optimal joint search strategies.
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- O. Gossner & N. Vieille, 2000.
"Strategic Learning in Games with Symmetric Information,"
THEMA Working Papers
2000-27, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- Gossner, Olivier & Vieille, Nicolas, 2003. "Strategic learning in games with symmetric information," Games and Economic Behavior, Elsevier, vol. 42(1), pages 25-47, January.
- GOSSNER, Olivier & VIEILLE, Nicolas, 1998. "Strategic learning in games with symmetric information," CORE Discussion Papers 1998023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Andreas Blume & John Duffy, 2004. "Organizational Learning: An Experimental Investigation," 2004 Meeting Papers 617, Society for Economic Dynamics.
- Thomas Wiseman, 2005. "A Partial Folk Theorem for Games with Unknown Payoff Distributions," Econometrica, Econometric Society, vol. 73(2), pages 629-645, 03.
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