Bounded rationality via recursion

13 years 11 months ago
Bounded rationality via recursion
Current trends in model construction in the field of agentbased computational economics base behavior of agents on either game theoretic procedures (e.g. belief learning, fictitious play, Bayesian learning) or are inspired by artificial intelligence (e.g. reinforcement learning). Evidence from experiments with human subjects puts the first approach in doubt, whereas the second one imposes significant computational and memory requirements on agents. In this paper, we introduce an efficient computational implementation of n-th order rationality using recursive simulation. An agent is n-th order rational if it determines its best response assuming that other agents are (n−1)-th order rational and zero-order agents behave according to a specified, non-strategic, rule. In recursive simulations, the simulated decision makers use simulation to inform their own decision making (search for best responses). Our goal is to provide agent modelers with an off-the-shelf implementation of n...
Maciej Latek, Robert L. Axtell, Bogumil Kaminski
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where ATAL
Authors Maciej Latek, Robert L. Axtell, Bogumil Kaminski
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