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Aspiration-based Perturbed Learning Automata in Weakly-Acyclic Games with Noisy Utility Measurements
Reinforcement-based learning dynamics may exhibit several limitations when applied in a distributed setup. In (repeatedly-played) multi-player/action strategic-form games, and when each player applies an independent copy of the learning dynamics, convergence to (usually desirable) pure Nash equilibr
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