Surprise Minimizing Multi-Agent Learning with Energy-based Models

Neural Information Processing Systems 

Multi-Agent Reinforcement Learning (MARL) has demonstrated significant success by virtue of collaboration across agents. Recent work, on the other hand, introduces surprise which quantifies the degree of change in an agent's environment.

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