Multi-Agent Systems

Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions ICML 2021 Provably efficient multi-task reinforcement learning with model transfer NeurIPS 2021 PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning ICML 2021 Quantile Bandits for Best Arms Identification ICML 2021 Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning ICML 2021 Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning IJCAI 2021 Regularized Softmax Deep Multi-Agent Q-Learning NeurIPS 2021 Reinforcement Learning Based Multi-Agent Resilient Control: From Deep Neural Networks to an Adaptive Law AAAI 2021 Reinforcement Learning for Mean Field Games with Strategic Complementarities AISTATS 2021 Resilient Multi-Agent Reinforcement Learning with Adversarial Value Decomposition AAAI 2021 RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract) AAAI 2021 RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents NeurIPS 2021 RODE: Learning Roles to Decompose Multi-Agent Tasks ICLR 2021 Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games NeurIPS 2021 Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot ICML 2021 Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing ICML 2021 Scaling Up Multi-Task Robotic Reinforcement Learning CoRL 2021 Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs ACL 2021 Settling the Variance of Multi-Agent Policy Gradients NeurIPS 2021 Social Interactions as Recursive MDPs CoRL 2021 Solving Common-Payoff Games with Approximate Policy Iteration AAAI 2021 Solving Partially Observable Stochastic Shortest-Path Games IJCAI 2021 Stabilizing Q Learning Via Soft Mellowmax Operator AAAI 2021 Strategically efficient exploration in competitive multi-agent reinforcement learning UAI 2021 Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning NeurIPS 2021