
The Advantage RegretMatching ActorCritic
Regret minimization has played a key role in online learning, equilibriu...
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Sound Search in Imperfect Information Games
Search has played a fundamental role in computer game research since the...
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Learning to Play NoPress Diplomacy with Best Response Policy Iteration
Recent advances in deep reinforcement learning (RL) have led to consider...
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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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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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A Generalized Training Approach for Multiagent Learning
This paper investigates a populationbased training regime based on game...
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OpenSpiel: A Framework for Reinforcement Learning in Games
OpenSpiel is a collection of environments and algorithms for research in...
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Neural Replicator Dynamics
In multiagent learning, agents interact in inherently nonstationary envi...
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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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αRank: MultiAgent Evaluation by Evolution
We introduce αRank, a principled evolutionary dynamics methodology, for...
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Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for MultiAgent Intelligence Research
Evolution has produced a multiscale mosaic of interacting adaptive unit...
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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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ActorCritic Policy Optimization in Partially Observable Multiagent Environments
Optimization of parameterized policies for reinforcement learning (RL) i...
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Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VRMCCFR) for Extensive Form Games using Baselines
Learning strategies for imperfect information games from samples of inte...
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Emergent Communication through Negotiation
Multiagent reinforcement learning offers a way to study how communicati...
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A Generalised Method for Empirical Game Theoretic Analysis
This paper provides theoretical bounds for empirical game theoretical an...
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Mastering Chess and Shogi by SelfPlay with a General Reinforcement Learning Algorithm
The game of chess is the most widelystudied domain in the history of ar...
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Symmetric Decomposition of Asymmetric Games
We introduce new theoretical insights into twopopulation asymmetric gam...
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A Unified GameTheoretic Approach to Multiagent Reinforcement Learning
To achieve general intelligence, agents must learn how to interact with ...
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ValueDecomposition Networks For Cooperative MultiAgent Learning
We study the problem of cooperative multiagent reinforcement learning w...
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Deep Qlearning from Demonstrations
Deep reinforcement learning (RL) has achieved several high profile succe...
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Multiagent Reinforcement Learning in Sequential Social Dilemmas
Matrix games like Prisoner's Dilemma have guided research on social dile...
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MemoryEfficient Backpropagation Through Time
We propose a novel approach to reduce memory consumption of the backprop...
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Convolution by Evolution: Differentiable Pattern Producing Networks
In this work we introduce a differentiable version of the Compositional ...
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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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NoRegret Learning in ExtensiveForm Games with Imperfect Recall
Counterfactual Regret Minimization (CFR) is an efficient noregret learn...
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