Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods

25 February 2021

Papers citing "Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods"

22 / 22 papers shown

Title
Exploring Explainable Multi-player MCTS-minimax Hybrids in Board Game Using Process Mining Yiyu Qian Tim Miller Zheng Qian Liyuan Zhao 37 0 0 30 Mar 2025
Towards Automated Semantic Interpretability in Reinforcement Learning via Vision-Language Models Zhaoxin Li Zhang Xi-Jia Batuhan Altundas Letian Chen Rohan R. Paleja Matthew C. Gombolay OffRL 41 0 0 20 Mar 2025
SySLLM: Generating Synthesized Policy Summaries for Reinforcement Learning Agents Using Large Language Models Sahar Admoni Omer Ben-Porat Ofra Amir LLMAG 49 0 0 13 Mar 2025
Learning Decision Trees as Amortized Structure Inference Mohammed Mahfoud Ghait Boukachab Michał Koziarski A. Garcia Stefan Bauer Yoshua Bengio Nikolay Malkin BDL 50 0 0 10 Mar 2025
In Search of Trees: Decision-Tree Policy Synthesis for Black-Box Systems via Search Emir Demirović Christian Schilling Anna Lukina 37 0 0 08 Jan 2025
Optimizing Interpretable Decision Tree Policies for Reinforcement Learning D. Vos Sicco Verwer OffRL 19 2 0 21 Aug 2024
Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning Hector Kohler Quentin Delfosse R. Akrour Kristian Kersting Philippe Preux 59 14 0 23 May 2024
Towards a Research Community in Interpretable Reinforcement Learning: the InterpPol Workshop Hector Kohler Quentin Delfosse Paul Festor Philippe Preux 27 0 0 16 Apr 2024
End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations Lirui Luo Guoxi Zhang Hongming Xu Yaodong Yang Cong Fang Qing Li 34 11 0 19 Mar 2024
Constraint-Generation Policy Optimization (CGPO): Nonlinear Programming for Policy Optimization in Mixed Discrete-Continuous MDPs Michael Gimelfarb Ayal Taitler Scott Sanner 18 0 0 20 Jan 2024
Limits of Actor-Critic Algorithms for Decision Tree Policies Learning in IBMDPs Hector Kohler R. Akrour Philippe Preux OffRL 16 2 0 23 Sep 2023
Interpretable Decision Tree Search as a Markov Decision Process Hector Kohler R. Akrour Philippe Preux 14 2 0 22 Sep 2023
Explainable Multi-Agent Reinforcement Learning for Temporal Queries Kayla Boggess Sarit Kraus Lu Feng LRM 19 11 0 17 May 2023
Optimal Interpretability-Performance Trade-off of Classification Trees with Black-Box Reinforcement Learning Hector Kohler R. Akrour Philippe Preux OffRL 12 1 0 11 Apr 2023
Optimal Decision Tree Policies for Markov Decision Processes D. Vos S. Verwer OffRL 19 8 0 30 Jan 2023
Fairness and Sequential Decision Making: Limits, Lessons, and Opportunities Samer B. Nashed Justin Svegliato Su Lin Blodgett FaML 30 6 0 13 Jan 2023
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges Yunpeng Qing Shunyu Liu Jie Song Huiqiong Wang Mingli Song XAI 25 1 0 12 Nov 2022
MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees Zichuan Liu Zichuan Liu Zhi Wang Yuanyang Zhu Chunlin Chen 55 5 0 15 Sep 2022
MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning Stephanie Milani Zhicheng Zhang Nicholay Topin Z. Shi Charles A. Kamhoua Evangelos E. Papalexakis Fei Fang OffRL 78 13 0 25 May 2022
A Survey of Explainable Reinforcement Learning Stephanie Milani Nicholay Topin Manuela Veloso Fei Fang XAI LRM 22 52 0 17 Feb 2022
A Survey on Interpretable Reinforcement Learning Claire Glanois Paul Weng Matthieu Zimmer Dong Li Tianpei Yang Jianye Hao Wulong Liu OffRL 21 91 0 24 Dec 2021
Particle Swarm Optimization for Generating Interpretable Fuzzy Reinforcement Learning Policies D. Hein A. Hentschel Thomas Runkler Steffen Udluft OffRL 28 78 0 19 Oct 2016