Reinforcement learning in Markovian evolutionary games

Borkar, V. S. (2002) Reinforcement learning in Markovian evolutionary games Advances in Complex Systems, 5 (1). pp. 55-72. ISSN 0219-5259

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A population of agents plays a stochastic dynamic game wherein there is an underlying state process with a Markovian dynamics that also affects their costs. A learning mechanism is proposed which takes into account intertemporal effects and incorporates an explicit process of expectation formation. The agents use this scheme to update their mixed strategies incrementally. The asymptotic behavior of this scheme is captured by an associated ordinary differential equation. Both the formulation and the analysis of the scheme draw upon the theory of reinforcement learning in artificial intelligence.

Item Type:Article
Source:Copyright of this article belongs to World Scientific Publishing Company.
Keywords:Evolutionary Games; Stochastic Dynamic Games; Expectation Formation; Actor-Critic Methods; Reinforcement Learning; Generalized Nash Equilibria
ID Code:81454
Deposited On:06 Feb 2012 05:04
Last Modified:06 Feb 2012 05:04

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