We consider an automated agent that needs to coordinate with a human partner when communication between them is not possible or is undesirable (tactic coordination games). Specifically, we examine situations where an agent and human attempt to coordinate their choices among several alternatives with equivalent utilities. We use machine learning algorithms to help the agent predict human choices in these tactic coordination domains.

Authors

• Inon Zuckerman
• Sarit Kraus Bar Ilan University
• Jeffrey S. Rosenschein

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