Current language models struggle with distributed team decision-making—they fail to effectively communicate and retrieve decision-relevant information. Training with reinforcement learning on final outcomes can improve coordination without explicit communication rewards.
TeamGym is a benchmark environment for training and evaluating AI agents on team decision-making tasks where information is distributed across participants. Using real-world data from legal, finance, medical, and software engineering domains, it measures how well language models share and integrate information.