Hector Kohler

According to our database, Hector Kohler authored at least 9 papers between 2023 and 2025.

Collaborative distances:

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

2025

Evaluating Interpretable Reinforcement Learning by Distilling Policies into Programs.

Hector Kohler, Quentin Delfosse, Waris Radji, Riad Akrour, Philippe Preux

CoRR, March, 2025

Breiman meets Bellman: Non-Greedy Decision Trees with MDPs.

Hector Kohler, Riad Akrour, Philippe Preux

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

2024

AdaStop: adaptive statistical testing for sound comparisons of Deep RL agents.

Timothée Mathieu, Matheus Centa, Riccardo Della Vecchia, Hector Kohler, Alena Shilova, Odalric-Ambrym Maillard, Philippe Preux

Trans. Mach. Learn. Res., 2024

Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning.

Hector Kohler, Quentin Delfosse, Riad Akrour, Kristian Kersting, Philippe Preux

CoRR, 2024

PID Tuning using Cross-Entropy Deep Learning: a Lyapunov Stability Analysis.

Hector Kohler, Benoît Clement, Thomas Chaffre, Gilles Le Chenadec

CoRR, 2024

Towards a Research Community in Interpretable Reinforcement Learning: the InterpPol Workshop.

Hector Kohler, Quentin Delfosse, Paul Festor, Philippe Preux

CoRR, 2024

2023

Discovering the Interpretability-Performance Pareto Front of Decision Trees with Dynamic Programming.

Hector Kohler, Riad Akrour, Philippe Preux

CoRR, 2023

AdaStop: sequential testing for efficient and reliable comparisons of Deep RL Agents.

Timothée Mathieu, Riccardo Della Vecchia, Alena Shilova, Matheus Centa de Medeiros, Hector Kohler, Odalric-Ambrym Maillard, Philippe Preux

CoRR, 2023

Optimal Interpretability-Performance Trade-off of Classification Trees with Black-Box Reinforcement Learning.

Hector Kohler, Riad Akrour, Philippe Preux

CoRR, 2023