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06/19/2022
The Power of Regularization in Solving Extensive-Form Games
In this paper, we investigate the power of regularization, a common tech...
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05/30/2022
Efficient Φ-Regret Minimization in Extensive-Form Games via Online Mirror Descent
A conceptually appealing approach for learning Extensive-Form Games (EFG...
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02/03/2022
Near-Optimal Learning of Extensive-Form Games with Imperfect Information
This paper resolves the open question of designing near-optimal algorith...
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10/27/2021
V-Learning – A Simple, Efficient, Decentralized Algorithm for Multiagent RL
A major challenge of multiagent reinforcement learning (MARL) is the cur...
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06/07/2021
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces
Modern reinforcement learning (RL) commonly engages practical problems w...
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02/05/2021
Provably Efficient Algorithms for Multi-Objective Competitive RL
We study multi-objective reinforcement learning (RL) where an agent's re...
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10/28/2020
Provably Efficient Online Agnostic Learning in Markov Games
We study online agnostic learning, a problem that arises in episodic mul...
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10/04/2020
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Model-based algorithms—algorithms that decouple learning of the model an...
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06/22/2020
Near-Optimal Reinforcement Learning with Self-Play
This paper considers the problem of designing optimal algorithms for rei...
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06/11/2020
A General Framework for Analyzing Stochastic Dynamics in Learning Algorithms
We present a general framework for analyzing high-probability bounds for...
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02/07/2020
Reward-Free Exploration for Reinforcement Learning
Exploration is widely regarded as one of the most challenging aspects of...
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07/22/2019
Efficient Policy Learning for Non-Stationary MDPs under Adversarial Manipulation
A Markov Decision Process (MDP) is a popular model for reinforcement lea...
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06/26/2019
Near Optimal Stratified Sampling
The performance of a machine learning system is usually evaluated by usi...
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02/22/2018