Learning Cross-Context Teammate Signatures for Zero-Shot Coordination

Zero shot coordination studies how agents cooperate with previously unseen teammates. A key challenge is to determine what information in interaction history actually matters for coordination, since teammate behavior is often entangled with the situations encountered. We argue that teammate representations should preserve coordination relevant conditional behavior rather than identity differences alone. We propose FSIG, which learns functional signatures by comparing teammate action predictions under shared queries. Behavioral supervision grounds these predictions in observed actions, while a consistency objective encourages agreement across matched histories. The learned signature then conditions the ego policy for adaptive coordination with unseen teammates. Across nine tasks spanning classic Overcooked, OvercookedV2, and Level Based Foraging, FSIG achieves competitive coordination performance. Further analyses show that interaction history provides additional predictive information, the functional consistency objective improves agreement across histories, and learned signatures affect controller behavior during coordination.