Toward Interpretable Deep Reinforcement Learning with Linear Model
U-Trees

Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees

16 July 2018

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Papers citing "Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees"

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Title
Neural-to-Tree Policy Distillation with Policy Improvement Criterion Zhaorong Li Yang Yu Yingfeng Chen Ke Chen Zhipeng Hu Changjie Fan 38 5 0 16 Aug 2021
Discovering User-Interpretable Capabilities of Black-Box Planning Agents Pulkit Verma Shashank Rao Marpally Siddharth Srivastava ELM LLMAG 76 20 0 28 Jul 2021
Feature-Based Interpretable Reinforcement Learning based on State-Transition Models Omid Davoodi Majid Komeili FAtt OffRL 61 6 0 14 May 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 245 678 0 20 Mar 2021
RLTIR: Activity-based Interactive Person Identification based on Reinforcement Learning Tree Qingyang Li Zhiwen Yu L. Yao Bin Guo 18 4 0 20 Mar 2021
CDT: Cascading Decision Trees for Explainable Reinforcement Learning Zihan Ding Pablo Hernandez-Leal G. Ding Changjian Li Ruitong Huang 65 21 0 15 Nov 2020
Domain-Level Explainability -- A Challenge for Creating Trust in Superhuman AI Strategies Jonas Andrulis Ole Meyer Grégory Schott Samuel Weinbach V. Gruhn 39 4 0 12 Nov 2020
Designing Interpretable Approximations to Deep Reinforcement Learning Nathan Dahlin K. C. Kalagarla Nikhil Naik Rahul Jain Pierluigi Nuzzo 59 9 0 28 Oct 2020
Towards Interpretable-AI Policies Induction using Evolutionary Nonlinear Decision Trees for Discrete Action Systems Yashesh D. Dhebar Kalyanmoy Deb S. Nageshrao Ling Zhu Dimitar Filev 68 16 0 20 Sep 2020
TripleTree: A Versatile Interpretable Representation of Black Box Agents and their Environments Tom Bewley J. Lawry FAtt 74 27 0 10 Sep 2020
Identifying Critical States by the Action-Based Variance of Expected Return Izumi Karino Yoshiyuki Ohmura Yasuo Kuniyoshi OffRL 13 2 0 26 Aug 2020
Am I Building a White Box Agent or Interpreting a Black Box Agent? Tom Bewley 27 1 0 02 Jul 2020
Automatic Discovery of Interpretable Planning Strategies Julian Skirzyñski Frederic Becker Falk Lieder 90 15 0 24 May 2020
Explainable Reinforcement Learning: A Survey Erika Puiutta Eric M. S. P. Veith XAI 105 248 0 13 May 2020
Learning an Interpretable Traffic Signal Control Policy James Ault Josiah P. Hanna Guni Sharon 45 50 0 23 Dec 2019
Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration Ritesh Noothigattu Djallel Bouneffouf Nicholas Mattei Rachita Chandra Piyush Madan Kush R. Varshney Murray Campbell Moninder Singh F. Rossi AI4CE 65 23 0 21 Sep 2018