Shaping Zero-Shot Coordination via State Blocking
For multi-agent systems requiring cooperation with unseen partners, SBC offers a simple method to improve generalization without environment modification.
State-Blocked Coordination (SBC) improves zero-shot coordination by generating diverse interaction scenarios via state blocking, achieving superior performance across benchmarks including strong generalization to human partners.
Zero-shot coordination (ZSC) aims to enable agents to cooperate with independently trained partners without prior interaction, a key requirement for real-world multi-agent systems and human-AI collaboration. Existing approaches have largely emphasized increasing partner diversity during training, yet such strategies often fall short of achieving reliable generalization to unseen partners. We introduce State-Blocked Coordination (SBC), a simple yet effective framework that improves ZSC by inducing diverse interaction scenarios without direct environment modification. Specifically, SBC generates a family of virtual environments through state blocking, allowing agents to experience a wide range of suboptimal partner policies. Across multiple benchmarks, SBC demonstrates superior performance in zero-shot coordination, including strong generalization to human partners.