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06/26/2023
On Imitation in Mean-field Games
We explore the problem of imitation learning (IL) in the context of mean...
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06/13/2023
Provably Learning Nash Policies in Constrained Markov Potential Games
Multi-agent reinforcement learning (MARL) addresses sequential decision-...
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06/12/2023
Cancellation-Free Regret Bounds for Lagrangian Approaches in Constrained Markov Decision Processes
Constrained Markov Decision Processes (CMDPs) are one of the common ways...
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10/20/2022
Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions
Policy Optimization (PO) algorithms have been proven particularly suited...
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10/10/2022
Do you pay for Privacy in Online learning?
Online learning, in the mistake bound model, is one of the most fundamen...
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07/18/2022
Active Exploration for Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is a powerful paradigm for inferrin...
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07/15/2020
Inverse Reinforcement Learning from a Gradient-based Learner
Inverse Reinforcement Learning addresses the problem of inferring an exp...
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07/15/2020
Newton-based Policy Optimization for Games
Many learning problems involve multiple agents optimizing different inte...
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11/20/2018
