3 papers
cs.LG2026
Hierarchical Support Vector State Partitioning for Distilling Black Box Reinforcement Learning Policies
Senne Deproost, Mehrdad Asadi, Ann Nowé
We introduce State Vector Space Partitioning (SVSP), a novel method to mimic a black box reinforcement learning policy using a set of human-interpretable subpolicies. By partitioni…
cs.LG2025
Explainable RL Policies by Distilling to Locally-Specialized Linear Policies with Voronoi State Partitioning
Senne Deproost, Dennis Steckelmacher, Ann Nowé
Deep Reinforcement Learning is one of the state-of-the-art methods for producing near-optimal system controllers. However, deep RL algorithms train a deep neural network, that lack…
cs.LG2024
Human-Readable Programs as Actors of Reinforcement Learning Agents Using Critic-Moderated Evolution
Senne Deproost, Denis Steckelmacher, Ann Nowé
With Deep Reinforcement Learning (DRL) being increasingly considered for the control of real-world systems, the lack of transparency of the neural network at the core of RL becomes…