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03/09/2023
Reward Informed Dreamer for Task Generalization in Reinforcement Learning
A long-standing goal of reinforcement learning is that algorithms can le...
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11/02/2022
Model-based Reinforcement Learning with a Hamiltonian Canonical ODE Network
Model-based reinforcement learning usually suffers from a high sample co...
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09/15/2022
On the Reuse Bias in Off-Policy Reinforcement Learning
Importance sampling (IS) is a popular technique in off-policy evaluation...
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06/09/2022
Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk
Though deep reinforcement learning (DRL) has obtained substantial succes...
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03/13/2022
Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model
In high-stake scenarios like medical treatment and auto-piloting, it's r...
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07/29/2021
Tianshou: a Highly Modularized Deep Reinforcement Learning Library
We present Tianshou, a highly modularized python library for deep reinfo...
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01/27/2019
Reward Shaping via Meta-Learning
Reward shaping is one of the most effective methods to tackle the crucia...
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10/10/2018
Lazy-CFR: a fast regret minimization algorithm for extensive games with imperfect information
In this paper, we focus on solving two-player zero-sum extensive games w...
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02/25/2018
Bayesian inverse problems with partial observations
We study a nonparametric Bayesian approach to linear inverse problems un...
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02/25/2018
