ASPIRATION-BASED REINFORCEMENT LEARNING IN REPEATED INTERACTION GAMES: AN OVERVIEW
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Publication:2772849
DOI10.1142/S0219198901000348zbMath0989.91502MaRDI QIDQ2772849
Dilip Mookherjee, Debraj Ray, Jonathan Bendor
Publication date: 19 February 2002
Published in: International Game Theory Review (Search for Journal in Brave)
Related Items (12)
Heterogeneous aspiration resolves social dilemma in structured populations ⋮ Muddling through: Noisy equilibrium selection ⋮ A dynamic foundation of the Rawlsian maxmin criterion ⋮ Satisficing leads to cooperation in mutual interests games ⋮ Aspiration adaptation in the ultimatum minigame. ⋮ A gradient-based reinforcement learning model of market equilibration ⋮ Popularity of reinforcement-based and belief-based learning models: an evolutionary approach ⋮ Transient and asymptotic dynamics of reinforcement learning in games ⋮ Mathematical modeling of learning from an inconsistent source: a nonlinear approach ⋮ No switchbacks: Rethinking aspiration-based dynamics in the ultimatum game ⋮ Synergistic effects of self-optimization and imitation rules on the evolution of cooperation in the investor sharing game ⋮ Stochastic Loss Aversion for Random Medium Access
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- Convergence of aspirations and (partial) cooperation in the prisoner's dilemma
- Boundedly rational rule learning in a guessing game
- Experience-weighted Attraction Learning in Normal Form Games
- Epistemic Conditions for Nash Equilibrium
- Case-Based Decision Theory
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