Lucas Lehnert

According to our database, Lucas Lehnert authored at least 15 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping.

Lucas Lehnert, Sainbayar Sukhbaatar, Paul McVay, Michael Rabbat, Yuandong Tian

CoRR, 2024

2023

IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control.

Rohan Chitnis, Yingchen Xu, Bobak Hashemi, Lucas Lehnert, Ürün Dogan, Zheqing Zhu, Olivier Delalleau

CoRR, 2023

Maximum State Entropy Exploration using Predecessor and Successor Representations.

Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Reward-Predictive Clustering.

Lucas Lehnert, Michael J. Frank, Michael L. Littman

CoRR, 2022

2021

Encoding Reusable Knowledge in State Representations.

Lucas Lehnert

PhD thesis, 2021

2020

Reward-predictive representations generalize across tasks in reinforcement learning.

Lucas Lehnert, Michael L. Littman, Michael J. Frank

PLoS Comput. Biol., 2020

Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning.

Lucas Lehnert, Michael L. Littman

J. Mach. Learn. Res., 2020

2019

Successor Features Support Model-based and Model-free Reinforcement Learning.

Lucas Lehnert, Michael L. Littman

CoRR, 2019

2018

Mitigating Planner Overfitting in Model-Based Reinforcement Learning.

Dilip Arumugam, David Abel, Kavosh Asadi, Nakul Gopalan, Christopher Grimm, Jun Ki Lee, Lucas Lehnert, Michael L. Littman

CoRR, 2018

Transfer with Model Features in Reinforcement Learning.

Lucas Lehnert, Michael L. Littman

CoRR, 2018

State Abstractions for Lifelong Reinforcement Learning.

David Abel, Dilip Arumugam, Lucas Lehnert, Michael L. Littman

Proceedings of the 35th International Conference on Machine Learning, 2018

On Value Function Representation of Long Horizon Problems.

Lucas Lehnert, Romain Laroche, Harm van Seijen

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Advantages and Limitations of using Successor Features for Transfer in Reinforcement Learning.

Lucas Lehnert, Stefanie Tellex, Michael L. Littman

CoRR, 2017

2015

Policy Gradient Methods for Off-policy Control.

Lucas Lehnert, Doina Precup

CoRR, 2015

2014

Connection Forms for Beating the Heart - LV Mechanics Challenge (Methods).

Arthur Mensch, Emmanuel Piuze, Lucas Lehnert, Adrianus J. Bakermans, Jon Sporring, Gustav J. Strijkers, Kaleem Siddiqi

Proceedings of the Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges, 2014