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- ISIDORE Id: 10670/1.1b189a...
- hal: hal-01052800
- doi: 10.1016/j.jebo.2008.03.014
- SCIENCESPO: 2441/9832
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jebo.2008.03.014
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info:eu-repo/semantics/altIdentifier/hdl/2441/9832
info:eu-repo/semantics/OpenAccess
Mots-clés
Artificial neural networks Prisoner's Dilemma Cooperation Firm learning C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation Modeling C - Mathematical and Quantitative Methods/C.C7 - Game Theory and Bargaining Theory/C.C7.C72 - Noncooperative Games D - Microeconomics/D.D2 - Production and Organizations/D.D2.D21 - Firm Behavior: Theory D - Microeconomics/D.D8 - Information, Knowledge, and Uncertainty/D.D8.D83 - Search • Learning • Information and Knowledge • Communication • Belief • Unawareness L - Industrial Organization/L.L1 - Market Structure, Firm Strategy, and Market Performance/L.L1.L13 - Oligopoly and Other Imperfect MarketsCiter ce document
Jason Barr et al., « Organization, learning and cooperation », Archive ouverte de Sciences Po (SPIRE), ID : 10.1016/j.jebo.2008.03.014
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Résumé
This paper models the organization of the firm as a type of artificial neural network in a duopoly setting. The firm plays a repeated Prisoner's Dilemma type game, and must also learn to map environmental signals to demand parameters and to its rival's willingness to cooperate. We study the prospects for cooperation given the need for the firm to learn the environment and its rival's output. We show how profit and cooperation rates are affected by the sizes of both firms, their willingness to cooperate, and by environmental complexity. In addition, we investigate equilibrium firm size and cooperation rates.
