Oren Gal

MATES: Learning Multi-Agent Interactions by Transforming Observations for Frozen Single-Agent Policies

Multi-agent reinforcement learning (MARL) commonly trains decentralized policies from scratch, requiring agents to acquire individual task competence and coordination simultaneously. Yet many multi-agent problems admit a compatible single-agent counterpart in which the underlying task can be learned in isolation. We in...