18 citations · 29 across the 16 of their papers we have counts for
3 papers · 1 filter
Limits of Actor-Critic Algorithms for Decision Tree Policies Learning in IBMDPs
Hector Kohler, Riad Akrour, Philippe Preux
Interpretability of AI models allows for user safety checks to build trust in such AIs. In particular, Decision Trees (DTs) provide a global look at the learned model and transpare…
Breiman meets Bellman: Non-Greedy Decision Trees with MDPs
Hector Kohler, Riad Akrour, Philippe Preux
In supervised learning, decision trees are valued for their interpretability and performance. While greedy decision tree algorithms like CART remain widely used due to their comput…
Optimal Interpretability-Performance Trade-off of Classification Trees with Black-Box Reinforcement Learning
Hector Kohler, Riad Akrour, Philippe Preux
Interpretability of AI models allows for user safety checks to build trust in these models. In particular, decision trees (DTs) provide a global view on the learned model and clear…