conftrace_

zero-sum game

190 papers

Explore in graph

Also known as

ZSG

Co-occurring keywords

nash equilibrium (398) game theory (854) multi-agent system (1819) markov game (86) regret bound (1926) online learning (1777) extensive-form game (86) multi-agent reinforcement learning (538) stochastic game (69) multi-agent learning (98)

Papers

Online Learning in Periodic Zero-Sum Games NIPS 2021
Matrix games with bandit feedback UAI 2021
Neural Auto-Curricula in Two-Player Zero-Sum Games NIPS 2021
Last Round Convergence and No-Dynamic Regret in Asymmetric Repeated Games ALT 2021
Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation IJCAI 2021
Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games NIPS 2021
Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent NIPS 2021
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization NIPS 2021
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach EMNLP 2021
Faster Game Solving via Predictive Blackwell Approachability: Connecting Regret Matching and Mirror Descent AAAI 2021
Minimax Adaptive Control for a Finite Set of Linear Systems L4DC 2021
Strategically efficient exploration in competitive multi-agent reinforcement learning UAI 2021
Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games AAAI 2021
Connecting Optimal Ex-Ante Collusion in Teams to Extensive-Form Correlation: Faster Algorithms and Positive Complexity Results ICML 2021
Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport ICML 2021
Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function AISTATS 2021
Mixed Nash Equilibria in the Adversarial Examples Game ICML 2021
Double Oracle Algorithm for Computing Equilibria in Continuous Games AAAI 2021
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization ICML 2021
Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games COLT 2021
Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems L4DC 2021
Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games COLT 2021
Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic Games ICML 2021
Reinforcement Learning for Constrained Markov Decision Processes AISTATS 2021
Randomization matters How to defend against strong adversarial attacks ICML 2020