Data to 7 Oct 2026

Combining Deep Reinforcement Learning and Search for Imperfect-Information Games

arXiv 2007.13544 ↗First posted 27 Jul 2020cs.GT cs.AI cs.LGcited by 110

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Abstract (arXiv)

The combination of deep reinforcement learning and search at both training and test time is a powerful paradigm that has led to a number of successes in single-agent settings and perfect-information games, best exemplified by AlphaZero. However, prior algorithms of this form cannot cope with imperfect-information games. This paper presents ReBeL, a general framework for self-play reinforcement learning and search that provably converges to a Nash equilibrium in any two-player zero-sum game. In the simpler setting of perfect-information games, ReBeL reduces to an algorithm similar to AlphaZero. Results in two different imperfect-information games show ReBeL converges to an approximate Nash equilibrium. We also show ReBeL achieves superhuman performance in heads-up no-limit Texas hold'em poker, while using far less domain knowledge than any prior poker AI.

Key facts. Cited by 110 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jul 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 18; 2023: 15; 2024: 20; 2025: 21; 2026: 23.

110 papers.

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2024Large Language Monkeys: Scaling Inference Compute with Repeated Samplingcited by 946
2022Transformers are Sample-Efficient World Modelscited by 317
2024Beyond Autoregression: Fast LLMs via Self-Distillation Through Timecited by 73
2023Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4cited by 67
2021DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learningcited by 65
2022Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulationcited by 61
2021No-Press Diplomacy from Scratchcited by 31
2023Deciphering Digital Detectives: Understanding LLM Behaviors and Capabilities in Multi-Agent Mystery Gamescited by 29
2024A Survey on Self-play Methods in Reinforcement Learningcited by 26
2022ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regretcited by 24
2021Student of Games: A unified learning algorithm for both perfect and imperfect information gamescited by 22
2023DITTO: Offline Imitation Learning with World Modelscited by 20

38 more

2024PokerGPT: An End-to-End Lightweight Solver for Multi-Player Texas Hold'em via Large Language Modelcited by 20
2021Scalable Online Planning via Reinforcement Learning Fine-Tuningcited by 18
2021Solving Common-Payoff Games with Approximate Policy Iterationcited by 15
2023Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditionscited by 14
2022On the convergence of policy gradient methods to Nash equilibria in general stochastic gamescited by 13
2025Reevaluating Policy Gradient Methods for Imperfect-Information Gamescited by 13
2023Mastering Strategy Card Game (Legends of Code and Magic) via End-to-End Policy and Optimistic Smooth Fictitious Playcited by 10
2024Large Language Models as Agents in Two-Player Gamescited by 10
2024RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learningcited by 10
2025AssistanceZero: Scalably Solving Assistance Gamescited by 10
2024Efficient Multi-agent Reinforcement Learning by Planningcited by 9
2022HSVI can solve zero-sum Partially Observable Stochastic Gamescited by 8
2021Deep Learning for General Game Playing with Ludii and Polygamescited by 7
2021Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphscited by 7
2022DouZero+: Improving DouDizhu AI by Opponent Modeling and Coach-guided Learningcited by 7
2025Scalable Decision Making for Games of Imperfect Informationcited by 7
2022Efficiently Computing Nash Equilibria in Adversarial Team Markov Gamescited by 6
2023Abstracting Imperfect Information Away from Two-Player Zero-Sum Gamescited by 6
2023Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learningcited by 6
2023DanZero+: Dominating the GuanDan Game through Reinforcement Learningcited by 6
2026Real-Time Parallel Counterfactual Regret Minimizationcited by 6
2022Strategy Synthesis for Zero-Sum Neuro-Symbolic Concurrent Stochastic Gamescited by 5
2022Generalized Beliefs for Cooperative AIcited by 5
2022Approximating Discontinuous Nash Equilibrial Values of Two-Player General-Sum Differential Gamescited by 5
2022DanZero: Mastering GuanDan Game with Reinforcement Learningcited by 5
2024Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalitiescited by 5
2025General search techniques without common knowledge for imperfect-information games, and application to superhuman Fog of War chesscited by 5
2025Contrastive Representations for Temporal Reasoningcited by 5
2026PokerSkill: LLMs Can Play Expert-Level Poker without Training or Solverscited by 5
2021Deep Synoptic Monte Carlo Planning in Reconnaissance Blind Chesscited by 4
2022Public Information Representation for Adversarial Team Gamescited by 4
2022Self-Imitation Learning from Demonstrationscited by 4
2024Advancing Investment Frontiers: Industry-grade Deep Reinforcement Learning for Portfolio Optimizationcited by 4
2025Human-Level Competitive Pok'emon via Scalable Offline Reinforcement Learning with Transformerscited by 4
2026MEMO: Memory-Augmented Model Context Optimization for Robust Multi-Turn Multi-Agent LLM Gamescited by 4
2026Agents That Certify Their Own Exploits: Confidence-Scheduled Restricted Responses for Safe Opponent Exploitationcited by 4
2022A Survey of Decision Making in Adversarial Gamescited by 3
2025VGC-Bench: Towards Mastering Diverse Team Strategies in Competitive Pok'emoncited by 3

50 most cited of 110 All 110 (JSON)