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03/02/2023
Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning
Progress in fields of machine learning and adversarial planning has bene...
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03/02/2023
Learning not to Regret
Regret minimization is a key component of many algorithms for finding Na...
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02/01/2023
Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning
Multiagent reinforcement learning (MARL) has benefited significantly fro...
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10/05/2022
Game Theoretic Rating in N-player general-sum games with Equilibria
Rating strategies in a game is an important area of research in game the...
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09/22/2022
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments
The Game Theory Multi-Agent team at DeepMind studies several aspects...
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06/30/2022
Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning
We introduce DeepNash, an autonomous agent capable of learning to play t...
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06/12/2022
A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games
Algorithms designed for single-agent reinforcement learning (RL) general...
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06/08/2022
ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret
Recent techniques for approximating Nash equilibria in very large games ...
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05/31/2022
Simplex NeuPL: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games
Learning to play optimally against any mixture over a diverse set of str...
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05/24/2022
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games: Corrections
Hindsight rationality is an approach to playing general-sum games that p...
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01/19/2022
Anytime PSRO for Two-Player Zero-Sum Games
Policy space response oracles (PSRO) is a multi-agent reinforcement lear...
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12/06/2021
Player of Games
Games have a long history of serving as a benchmark for progress in arti...
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06/17/2021
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers
Two-player, constant-sum games are well studied in the literature, but t...
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06/02/2021
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent
Nash equilibrium is a central concept in game theory. Several Nash solve...
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02/13/2021
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games
Hindsight rationality is an approach to playing multi-agent, general-sum...
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01/11/2021
Solving Common-Payoff Games with Approximate Policy Iteration
For artificially intelligent learning systems to have widespread applica...
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12/10/2020
Hindsight and Sequential Rationality of Correlated Play
Driven by recent successes in two-player, zero-sum game solving and play...
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10/20/2020
Negotiating Team Formation Using Deep Reinforcement Learning
When autonomous agents interact in the same environment, they must often...
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08/27/2020
The Advantage Regret-Matching Actor-Critic
Regret minimization has played a key role in online learning, equilibriu...
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06/15/2020
Sound Search in Imperfect Information Games
Search has played a fundamental role in computer game research since the...
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06/08/2020
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
Recent advances in deep reinforcement learning (RL) have led to consider...
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04/20/2020
Approximate exploitability: Learning a best response in large games
A common metric in games of imperfect information is exploitability, i.e...
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02/19/2020
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
In this paper we investigate the Follow the Regularized Leader dynamics ...
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09/27/2019
A Generalized Training Approach for Multiagent Learning
This paper investigates a population-based training regime based on game...
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08/26/2019
OpenSpiel: A Framework for Reinforcement Learning in Games
OpenSpiel is a collection of environments and algorithms for research in...
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06/01/2019
Neural Replicator Dynamics
In multiagent learning, agents interact in inherently nonstationary envi...
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03/13/2019
Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent
In this paper, we present exploitability descent, a new algorithm to com...
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03/04/2019
α-Rank: Multi-Agent Evaluation by Evolution
We introduce α-Rank, a principled evolutionary dynamics methodology, for...
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03/02/2019
Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research
Evolution has produced a multi-scale mosaic of interacting adaptive unit...
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02/01/2019
The Hanabi Challenge: A New Frontier for AI Research
From the early days of computing, games have been important testbeds for...
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10/21/2018
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments
Optimization of parameterized policies for reinforcement learning (RL) i...
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09/09/2018
Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games using Baselines
Learning strategies for imperfect information games from samples of inte...
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04/11/2018
Emergent Communication through Negotiation
Multi-agent reinforcement learning offers a way to study how communicati...
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03/16/2018
A Generalised Method for Empirical Game Theoretic Analysis
This paper provides theoretical bounds for empirical game theoretical an...
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12/05/2017
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
The game of chess is the most widely-studied domain in the history of ar...
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11/14/2017
Symmetric Decomposition of Asymmetric Games
We introduce new theoretical insights into two-population asymmetric gam...
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11/02/2017
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
To achieve general intelligence, agents must learn how to interact with ...
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06/16/2017
Value-Decomposition Networks For Cooperative Multi-Agent Learning
We study the problem of cooperative multi-agent reinforcement learning w...
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04/12/2017
Deep Q-learning from Demonstrations
Deep reinforcement learning (RL) has achieved several high profile succe...
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02/10/2017
Multi-agent Reinforcement Learning in Sequential Social Dilemmas
Matrix games like Prisoner's Dilemma have guided research on social dile...
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06/10/2016
Memory-Efficient Backpropagation Through Time
We propose a novel approach to reduce memory consumption of the backprop...
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06/08/2016
Convolution by Evolution: Differentiable Pattern Producing Networks
In this work we introduce a differentiable version of the Compositional ...
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06/02/2014
Monte Carlo Tree Search with Heuristic Evaluations using Implicit Minimax Backups
Monte Carlo Tree Search (MCTS) has improved the performance of game engi...
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05/03/2012