Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability

Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian

Abstract: Many real-world tasks involve multiple agents with partial observability and limited communication. Learning is challenging in these settings due to local viewpoints of agents, which perceive the w...