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2020 – today
- 2024
[c5]Rohan Chitnis, Yingchen Xu, Bobak Hashemi, Lucas Lehnert, Ürün Dogan, Zheqing Zhu, Olivier Delalleau:
IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control. ICRA 2024: 9154-9160- [i9]Lucas Lehnert, Sainbayar Sukhbaatar, Paul McVay, Michael Rabbat, Yuandong Tian:
Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping. CoRR abs/2402.14083 (2024) - 2023
- [c4]Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth:
Maximum State Entropy Exploration using Predecessor and Successor Representations. NeurIPS 2023 - [i8]Rohan Chitnis, Yingchen Xu, Bobak Hashemi, Lucas Lehnert, Ürün Dogan, Zheqing Zhu, Olivier Delalleau:
IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control. CoRR abs/2306.00867 (2023) - [i7]Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth:
Maximum State Entropy Exploration using Predecessor and Successor Representations. CoRR abs/2306.14808 (2023) - 2022
- [i6]Lucas Lehnert, Michael J. Frank, Michael L. Littman:
Reward-Predictive Clustering. CoRR abs/2211.03281 (2022) - 2021
- [b1]Lucas Lehnert:
Encoding Reusable Knowledge in State Representations. Brown University, USA, 2021 - 2020
- [j2]Lucas Lehnert, Michael L. Littman:
Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning. J. Mach. Learn. Res. 21: 196:1-196:53 (2020) - [j1]Lucas Lehnert
, Michael L. Littman, Michael J. Frank:
Reward-predictive representations generalize across tasks in reinforcement learning. PLoS Comput. Biol. 16(10) (2020)
2010 – 2019
- 2019
- [i5]Lucas Lehnert, Michael L. Littman:
Successor Features Support Model-based and Model-free Reinforcement Learning. CoRR abs/1901.11437 (2019) - 2018
- [c3]Lucas Lehnert, Romain Laroche, Harm van Seijen:
On Value Function Representation of Long Horizon Problems. AAAI 2018: 3457-3465 - [c2]David Abel, Dilip Arumugam, Lucas Lehnert, Michael L. Littman:
State Abstractions for Lifelong Reinforcement Learning. ICML 2018: 10-19 - [i4]Lucas Lehnert, Michael L. Littman:
Transfer with Model Features in Reinforcement Learning. CoRR abs/1807.01736 (2018) - [i3]Dilip Arumugam, David Abel, Kavosh Asadi, Nakul Gopalan, Christopher Grimm, Jun Ki Lee, Lucas Lehnert, Michael L. Littman:
Mitigating Planner Overfitting in Model-Based Reinforcement Learning. CoRR abs/1812.01129 (2018) - 2017
- [i2]Lucas Lehnert, Stefanie Tellex, Michael L. Littman:
Advantages and Limitations of using Successor Features for Transfer in Reinforcement Learning. CoRR abs/1708.00102 (2017) - 2015
- [i1]Lucas Lehnert, Doina Precup:
Policy Gradient Methods for Off-policy Control. CoRR abs/1512.04105 (2015) - 2014
- [c1]Arthur Mensch, Emmanuel Piuze, Lucas Lehnert, Adrianus J. Bakermans, Jon Sporring, Gustav J. Strijkers, Kaleem Siddiqi:
Connection Forms for Beating the Heart - LV Mechanics Challenge (Methods). STACOM 2014: 83-92
Coauthor Index
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