multi-agent learning

Communication-Efficient Collaborative Best Arm Identification AAAI 2023 Cooperative Multi-Agent Learning in a Complex World: Challenges and Solutions AAAI 2023 Higher-Order Uncoupled Dynamics Do Not Lead to Nash Equilibrium - Except When They Do NeurIPS 2023 Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium IJCAI 2023 Learning Rationalizable Equilibria in Multiplayer Games ICLR 2023 Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity JMLR 2023 Multi-Agent Learning with Heterogeneous Linear Contextual Bandits NeurIPS 2023 Online Corrupted User Detection and Regret Minimization NeurIPS 2023 Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games ICML 2023 Policy Space Diversity for Non-Transitive Games NeurIPS 2023 Regret Minimization and Convergence to Equilibria in General-sum Markov Games ICML 2023 Safe Multi-agent Learning via Trapping Regions IJCAI 2023 Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence AISTATS 2023 The Impact of Exploration on Convergence and Performance of Multi-Agent Q-Learning Dynamics ICML 2023 Towards a Better Understanding of Learning with Multiagent Teams IJCAI 2023 A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization NeurIPS 2022 Balancing adaptability and non-exploitability in repeated games UAI 2022 COLA: Consistent Learning with Opponent-Learning Awareness ICML 2022 Cooperative Online Learning in Stochastic and Adversarial MDPs ICML 2022 Equilibrium Learning in Auction Markets AAAI 2022 Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback NeurIPS 2022 For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria ICML 2022 Greedy when Sure and Conservative when Uncertain about the Opponents ICML 2022 Learning From All Vehicles CVPR 2022 Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits ICML 2022