title: Coupled replicator equations for the dynamics of learning in multiagent systems.
abstract: Starting with a group of reinforcement-learning agents we derive coupled replicator equations that describe the dynamics of collective learning in multiagent systems. We show that, although agents model their environment in a self-interested way without sharing knowledge, a game dynamics emerges naturally through environment-mediated interactions. An application to rock-scissors-paper game interactions shows that the collective learning dynamics exhibits a diversity of competitive and cooperative behaviors. These include quasiperiodicity, stable limit cycles, intermittency, and deterministic chaos-behaviors that should be expected in heterogeneous multiagent systems described by the general replicator equations we derive.
authors.affiliation: Brain Science Institute, Institute of Physical and Chemical Research (RIKEN), 2-1 Hirosawa, Saitama 351-0198, Japan. ysato@bdc.brain.riken.go.jp
authors.forename: Yuzuru
authors.initials: Y
authors.lastname: Sato
authors.forename: James P
authors.initials: JP
authors.lastname: Crutchfield