Methods

Multi-agent assignment via state augmented reinforcement learning L4DC 2024 Multi-Agent Domain Calibration with a Handful of Offline Data NeurIPS 2024 Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces AAAI 2024 Multi-Agent Imitation Learning: Value is Easy, Regret is Hard NeurIPS 2024 Multi-Agent Learning in Contextual Games under Unknown Constraints AISTATS 2024 Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy ICML 2024 Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing ICML 2024 Multi-agent Reinforcement Learning with Hybrid Action Space for Free Gait Motion Planning of Hexapod Robots CoRL 2024 Multi-Reward Best Policy Identification NeurIPS 2024 Multi-Task Interactive Robot Fleet Learning with Visual World Models CoRL 2024 Multi-world Model in Continual Reinforcement Learning AAAI 2024 MusicRL: Aligning Music Generation to Human Preferences ICML 2024 N-agent Ad Hoc Teamwork NeurIPS 2024 N-Agent Ad Hoc Teamwork IJCAI 2024 Nash Learning from Human Feedback ICML 2024 Natural Language-based State Representation in Deep Reinforcement Learning NAACL 2024 Navigating Noisy Feedback: Enhancing Reinforcement Learning with Error-Prone Language Models EMNLP 2024 Navigating Uncertainty in Epidemic Contexts with Reinforcement Learning AAAI 2024 Near-continuous time Reinforcement Learning for continuous state-action spaces ALT 2024 Near-Optimal Distributionally Robust Reinforcement Learning with General L_p Norms NeurIPS 2024 Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs NeurIPS 2024 Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games AISTATS 2024 Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback ICML 2024 Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints ICML 2024 NeoRL: Efficient Exploration for Nonepisodic RL NeurIPS 2024