Learning Quantitative Knowledge for Multiagent Coordination
نویسندگان
چکیده
A central challenge of multiagent coordination is reasoning about how the actions of one agent affect the actions of another. Knowledge of these interrelationships can help coordinate agents -preventing conflicts and exploiting beneficial relationships among actions. We explore three interlocking methods that learn quantitative knowledge of such non-local effects in T/EMS, a well-developed framework for multiagent coordination. The surprising simplicity and effectiveness of these methods demonstrates how agents can learn domain-specific knowledge quickly, extending the utility of coordination frameworks that explicitly represent coordination knowledge.
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