The United Nations' 2030 Agenda for Sustainable Development requires all countries to collaborate against adversarial factors, a scenario that can be formalized as an adversarial team game. However, existing solution concepts assume team players share identical utility functions---an assumption inconsistent with real-world settings where countries have divergent objectives. This paper argues that studying adversarial team games must account for heterogeneous utilities among team players. We show that ignoring utility differences can render computed equilibria unstable in the original game, and we formalize this degradation via the Price of Ignoring Heterogeneity, which can be unbounded. To address this, we introduce the Co-opetition Equilibrium (CoE), where team players with heterogeneous utilities correlate their strategies (cooperation) against an adversary (competition). We establish existence via reduction from Nash equilibrium, and prove that finding a CoE is PPAD-complete while computing a Team-Maximizing CoE (TMCoE) is NP-hard. Nevertheless, we identify a broad class of zero-sum adversarial team games---those satisfying a consistent-constraint condition that generalizes identical utilities---where TMCoEs are exchangeable and computable in polynomial time via linear programming. We outline directions for algorithm design, MARL, and extensions to extensive-form and multi-team games.

翻译：暂无翻译