Improving Agent Behaviors with RL Fine-Tuning for Autonomous Driving.
Proceedings of the Computer Vision - ECCV 2024, 2024
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research.
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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios.
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IROS, 2023
CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
Context-Aware Language Modeling for Goal-Oriented Dialogue Systems.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving.
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Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022
Offline Learning for Scalable Decision Making
PhD thesis, 2021
Evaluating Strategic Structures in Multi-Agent Inverse Reinforcement Learning.
J. Artif. Intell. Res., 2021
Learning to Reach Goals via Iterated Supervised Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation.
Proceedings of the 9th International Conference on Learning Representations, 2021
Benchmarks for Deep Off-Policy Evaluation.
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Proceedings of the 9th International Conference on Learning Representations, 2021
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.
CoRR, 2020
D4RL: Datasets for Deep Data-Driven Reinforcement Learning.
CoRR, 2020
Learning To Reach Goals Without Reinforcement Learning.
CoRR, 2019
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction.
CoRR, 2019
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
When to Trust Your Model: Model-Based Policy Optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Diagnosing Bottlenecks in Deep Q-learning Algorithms.
Proceedings of the 36th International Conference on Machine Learning, 2019
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following.
Proceedings of the 7th International Conference on Learning Representations, 2019
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Learning Robust Rewards with Adverserial Inverse Reinforcement Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018
Learning Robust Rewards with Adversarial Inverse Reinforcement Learning.
CoRR, 2017
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Generalizing Skills with Semi-Supervised Reinforcement Learning.
Proceedings of the 5th International Conference on Learning Representations, 2017
One-shot learning of manipulation skills with online dynamics adaptation and neural network priors.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016