Ying-Dong Lu

Independent Multi-Agent Reinforcement Learning with Counterfactual Semantic-Social World Models

Fully decentralized multi-agent reinforcement learning (MARL), also referred to as independent learning, requires each agent to learn and act using only its local information and experience, without a centralized critic or inter-agent communication. Such a stringent information structure renders the conventional reward...