Adaptive learning in systems of interacting agents.
A learning rule is adaptive if it is simple to compute, requires little information about the actions of others, and is plausible as a model of behavior [1, 2]. In this paper I survey a family of adaptive learning rules in which experimentation plays a key role. These rules have the property that, in large classes of games, agents' individual behavior results in Nash equilibrium behavior by the group a high proportion of the time. Agents need not know that Nash equilibrium is being played - i...Expand abstract
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