Multi-Model Training for Multi-Agent Communication Skills (Elias Stengel-Eskin)

As we scale from individual agents to teams of agents, inter-agent communication will become increasingly important. In this talk, I will describe a general paradigm for teaching multi-agent communication skills through multi-model reinforcement learning, which I will illustrate via three key collaborative skills: expressing confidence in a calibrated way, responding robustly to positive and negative persuasion, and expressing reasoning faithfully. I will show how these problems can be framed in terms of speaker-listener games, and how this framing allows us to teach models collaborative skills, often using games simulated on smaller models to train larger models.