nash equilibrium

Inferring Objectives in Continuous Dynamic Games from Noise-Corrupted Partial State Observations RSS 2021 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport ICML 2021 Large-Scale Multi-Agent Deep FBSDEs ICML 2021 Last-iterate Convergence in Extensive-Form Games NeurIPS 2021 Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games COLT 2021 Learning Game-Theoretic Models of Multiagent Trajectories Using Implicit Layers AAAI 2021 Learning in Matrix Games can be Arbitrarily Complex COLT 2021 Learning in Multi-Player Stochastic Games UAI 2021 Learning in Nonzero-Sum Stochastic Games with Potentials ICML 2021 Learning in two-player zero-sum partially observable Markov games with perfect recall NeurIPS 2021 Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation IJCAI 2021 Learning While Playing in Mean-Field Games: Convergence and Optimality ICML 2021 Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions AISTATS 2021 Mean Field Games Flock! The Reinforcement Learning Way IJCAI 2021 Minimax sample complexity for turn-based stochastic game UAI 2021 Model-Free Online Learning in Unknown Sequential Decision Making Problems and Games AAAI 2021 Modeling Precomputation In Games Played Under Computational Constraints IJCAI 2021 Multiplayer Bandit Learning, from Competition to Cooperation COLT 2021 Multi-Scale Games: Representing and Solving Games on Networks with Group Structure AAAI 2021 Newton Optimization on Helmholtz Decomposition for Continuous Games AAAI 2021 On Characterizing GAN Convergence Through Proximal Duality Gap ICML 2021 One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning ICML 2021 Online Learning for Load Balancing of Unknown Monotone Resource Allocation Games ICML 2021 On the Approximation of Nash Equilibria in Sparse Win-Lose Multi-player Games AAAI 2021 On the Rate of Convergence of Regularized Learning in Games: From Bandits and Uncertainty to Optimism and Beyond NeurIPS 2021