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Rong-Jun Qin

2 accepted papers

2023

Adversarial Counterfactual Environment Model Learning

NeurIPS 2023spotlight

An accurate environment dynamics model is crucial for various downstream tasks in sequential decision-making, such as counterfactual prediction, off-policy evaluation, and offline reinforcement learning. Currently, these models were learned through empirical risk minimization (ERM) by step-wise fit…

2022

NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning

NeurIPS 2022accept

Offline reinforcement learning (RL) aims at learning effective policies from historical data without extra environment interactions. During our experience of applying offline RL, we noticed that previous offline RL benchmarks commonly involve significant reality gaps, which we have identified includ…