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Learning in games by random sampling
Friedman, James W.; Mezzetti, Claudio - In: Journal of economic theory 98 (2001) 1, pp. 55-84
Persistent link: https://www.econbiz.de/10001584858
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Collusion in dynamic Bertrand oligopoly with correlated private signals and communication
Aoyagi, Masaki - In: Journal of economic theory 102 (2002) 1, pp. 229-248
Persistent link: https://www.econbiz.de/10001661311
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The dynamics of political compromise
Dixit, Avinash K.; Grossman, Gene M.; Gul, Faruk - In: Journal of political economy 108 (2000) 3, pp. 531-568
Persistent link: https://www.econbiz.de/10001485307
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Rationalizable foresight dynamics : evolution and rationalizability
Matsui, Akihiko (contributor); Oyama, Daisuke (contributor) - 2002 - [Elektronische Ressource]
Persistent link: https://www.econbiz.de/10002174821
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Strategic competition in oligopolies with fluctuating demand
Neubecker, Leslie - 2006
Persistent link: https://www.econbiz.de/10003115170
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Le critère de stabilité stochastique en théorie des jeux évolutionnaires
Baron, Richard; Solal, Philippe - In: Revue d'économie industrielle 114/115 (2006) 2/3, pp. 141-160
Persistent link: https://www.econbiz.de/10003405154
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Rationalizable foresight dynamics
Matsui, Akihiko; Oyama, Daisuke - In: Games and economic behavior 56 (2006) 2, pp. 299-322
Persistent link: https://www.econbiz.de/10003344072
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The role of information in repeated games with frequent actions
Sannikov, Yuliy; Skrzypacz, Andrzej - In: Econometrica : journal of the Econometric Society, an … 78 (2010) 3, pp. 847-882
Persistent link: https://www.econbiz.de/10003992573
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Strategic Competition in Oligopolies with Fluctuating Demand
Neubecker, Leslie (contributor) - 2006
theory is applied to integrate long-run decisions and different types of demand into the analysis. Aside from its …
Persistent link: https://www.econbiz.de/10013520515
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A Review of Stochastic Approximation
Nilaish, Nilaish - 2017
In this paper we review stochastic approximation algorithm dynamics commonly rise from scaling limits and its usage to treat big data with ideally noises. We observe that how to extract the incrementality to get useful convergences, low per iterates and memory requirements. Thus, leading to deal...
Persistent link: https://www.econbiz.de/10012959922