Search Results for author:
Found 4 papers, 1 papers with code
Quantifying Zero-shot Coordination Capability with Behavior Preferring Partners
Current evaluation methods for ZSC capability still need to improve in constructing diverse evaluation partners and comprehensively measuring the ZSC capability.
Order Matters: Agent-by-agent Policy Optimization
In this paper, we propose the \textbf{A}gent-by-\textbf{a}gent \textbf{P}olicy \textbf{O}ptimization (A2PO) algorithm to improve the sample efficiency and retain the guarantees of monotonic improvement for each agent during training.
Model-based Multi-agent Reinforcement Learning: Recent Progress and Prospects
Significant advances have recently been achieved in Multi-Agent Reinforcement Learning (MARL) which tackles sequential decision-making problems involving multiple participants.
Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts
We specify the dynamics sample complexity and the opponent sample complexity in MARL, and conduct a theoretic analysis of return discrepancy upper bound.
Multi-agent Reinforcement Learning
Reinforcement Learning (RL)
