Verifiable Reinforcement Learning via Policy Extraction

22 May 2018

Papers citing "Verifiable Reinforcement Learning via Policy Extraction"

50 / 167 papers shown

Title
Learning of Generalizable and Interpretable Knowledge in Grid-Based Reinforcement Learning Environments Manuel Eberhardinger Johannes Maucher S. Maghsudi 37 4 0 07 Sep 2023
On Reducing Undesirable Behavior in Deep Reinforcement Learning Models Ophir M. Carmel Guy Katz 40 0 0 06 Sep 2023
Neurosymbolic Reinforcement Learning and Planning: A Survey Kamal Acharya Waleed Raza Carlos Dourado Alvaro Velasquez Houbing Song NAI OffRL 32 16 0 02 Sep 2023
Learning to Identify Critical States for Reinforcement Learning from Videos Haozhe Liu Mingchen Zhuge Bing Li Yu‐Han Wang Francesco Faccio Guohao Li Jürgen Schmidhuber OffRL 28 6 0 15 Aug 2023
Synthesizing Programmatic Policies with Actor-Critic Algorithms and ReLU Networks S. Orfanos Levi H. S. Lelis 27 6 0 04 Aug 2023
Can You Improve My Code? Optimizing Programs with Local Search Fatemeh Abdollahi Saqib Ameen Matthew E. Taylor Levi H. S. Lelis 22 0 0 10 Jul 2023
Choosing Well Your Opponents: How to Guide the Synthesis of Programmatic Strategies Rubens O. Moraes David S. Aleixo Lucas N. Ferreira Levi H. S. Lelis 16 7 0 10 Jul 2023
Learning Interpretable Models of Aircraft Handling Behaviour by Reinforcement Learning from Human Feedback Tom Bewley J. Lawry Arthur G. Richards 30 1 0 26 May 2023
$N$\text{A}^\text{2}$Q: Neural Attention Additive Model for Interpretable Multi-Agent Q-Learning$ N $\text{A}^\text{2}$ Q: Neural Attention Additive Model for Interpretable Multi-Agent Q-Learning Zichuan Liu Yuanyang Zhu Chunlin Chen 47 10 0 26 Apr 2023
Reinforcement Learning with Knowledge Representation and Reasoning: A Brief Survey Chao Yu Xuejing Zheng H. Zhuo OffRL LRM 55 7 0 24 Apr 2023
How to Control Hydrodynamic Force on Fluidic Pinball via Deep Reinforcement Learning Haodong Feng Yue Wang Hui Xiang Zhiyang Jin Dixia Fan AI4CE 26 8 0 23 Apr 2023
Exact and Cost-Effective Automated Transformation of Neural Network Controllers to Decision Tree Controllers K. Chang Nathan Dahlin Rahul Jain Pierluigi Nuzzo OffRL 16 0 0 11 Apr 2023
Optimal Interpretability-Performance Trade-off of Classification Trees with Black-Box Reinforcement Learning Hector Kohler R. Akrour Philippe Preux OffRL 24 1 0 11 Apr 2023
Safe Reinforcement Learning via Probabilistic Logic Shields Wen-Chi Yang G. Marra Gavin Rens Luc de Raedt OffRL 46 30 0 06 Mar 2023
CrystalBox: Future-Based Explanations for Input-Driven Deep RL Systems Sagar Patel Sangeetha Abdu Jyothi Nina Narodytska OffRL 16 0 0 27 Feb 2023
Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles Songyang Han Shangli Zhou Lynn Pepin Jiangwei Wang Caiwen Ding Fei Miao 21 1 0 08 Feb 2023
Optimal Decision Tree Policies for Markov Decision Processes D. Vos S. Verwer OffRL 27 9 0 30 Jan 2023
Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs Guanhui. Liu En-Pei Hu Pu-Jen Cheng Hung-yi Lee Shao-Hua Sun 74 18 0 30 Jan 2023
Explainable Deep Reinforcement Learning: State of the Art and Challenges G. Vouros XAI 52 77 0 24 Jan 2023
XDQN: Inherently Interpretable DQN through Mimicking Andreas Kontogiannis G. Vouros 24 1 0 08 Jan 2023
Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search Wenqing Zheng S. Sharan Zhiwen Fan Kevin Wang Yihan Xi Zhangyang Wang 58 9 0 30 Dec 2022
On Transforming Reinforcement Learning by Transformer: The Development Trajectory Shengchao Hu Li Shen Ya Zhang Yixin Chen Dacheng Tao OffRL 30 25 0 29 Dec 2022
Decisions that Explain Themselves: A User-Centric Deep Reinforcement Learning Explanation System Xiaoran Wu Zihan Yan Chongjie Zhang Tongshuang Wu 24 1 0 01 Dec 2022
Explainable Action Advising for Multi-Agent Reinforcement Learning Yue (Sophie) Guo Joseph Campbell Simon Stepputtis Ruiyu Li Dana Hughes Fei Fang Katia Sycara 27 14 0 15 Nov 2022
(When) Are Contrastive Explanations of Reinforcement Learning Helpful? Sanjana Narayanan Isaac Lage Finale Doshi-Velez OffRL 12 1 0 14 Nov 2022
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges Yunpeng Qing Shunyu Liu Mingli Song Huiqiong Wang Mingli Song XAI 35 1 0 12 Nov 2022
ProtoX: Explaining a Reinforcement Learning Agent via Prototyping Ronilo Ragodos Tong Wang Qihang Lin Xun Zhou 24 7 0 06 Nov 2022
On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach Dennis L. Wei Rahul Nair Amit Dhurandhar Kush R. Varshney Elizabeth M. Daly Moninder Singh FAtt 38 9 0 02 Nov 2022
Neurosymbolic Motion and Task Planning for Linear Temporal Logic Tasks Xiaowu Sun Yasser Shoukry 48 11 0 11 Oct 2022
Reward Learning with Trees: Methods and Evaluation Tom Bewley J. Lawry Arthur G. Richards R. Craddock Ian Henderson 23 1 0 03 Oct 2022
Guiding Safe Exploration with Weakest Preconditions Greg Anderson Swarat Chaudhuri Işıl Dillig 46 6 0 28 Sep 2022
MSVIPER: Improved Policy Distillation for Reinforcement-Learning-Based Robot Navigation Aaron M. Roth Jing Liang Ram D. Sriram Elham Tabassi Tianyi Zhou 34 1 0 19 Sep 2022
There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes Yishay Mansour Michal Moshkovitz Cynthia Rudin FAtt 41 3 0 09 Jun 2022
GALOIS: Boosting Deep Reinforcement Learning via Generalizable Logic Synthesis Yushi Cao Zhiming Li Tianpei Yang Hao Zhang Yan Zheng Yi Li Jianye Hao Yang Liu NAI 38 16 0 27 May 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 83 13 0 25 May 2022
A Review of Safe Reinforcement Learning: Methods, Theory and Applications Shangding Gu Longyu Yang Yali Du Guang Chen Florian Walter Jun Wang Alois C. Knoll OffRL AI4TS 117 241 0 20 May 2022
Provably Safe Reinforcement Learning: Conceptual Analysis, Survey, and Benchmarking Hanna Krasowski Jakob Thumm Marlon Müller Lukas Schäfer Xiao Wang Matthias Althoff 88 20 0 13 May 2022
What can we Learn Even From the Weakest? Learning Sketches for Programmatic Strategies L. C. Medeiros David S. Aleixo Levi H. S. Lelis 24 15 0 22 Mar 2022
Safe Neurosymbolic Learning with Differentiable Symbolic Execution Chenxi Yang Swarat Chaudhuri 27 9 0 15 Mar 2022
Keeping Minimal Experience to Achieve Efficient Interpretable Policy Distillation Xiao Liu Shuyang Liu Wenbin Li Shangdong Yang Yang Gao OffRL 11 0 0 02 Mar 2022
A Survey of Explainable Reinforcement Learning Stephanie Milani Nicholay Topin Manuela Veloso Fei Fang XAI LRM 30 52 0 17 Feb 2022
Local Explanations for Reinforcement Learning Ronny Luss Amit Dhurandhar Miao Liu FAtt OffRL 16 3 0 08 Feb 2022
Learning Interpretable, High-Performing Policies for Autonomous Driving Rohan R. Paleja Yaru Niu Andrew Silva Chace Ritchie Sugju Choi Matthew C. Gombolay 27 16 0 04 Feb 2022
Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning Tongzhou Mu Kaixiang Lin Fei Niu Govind Thattai OffRL 25 0 0 21 Jan 2022
Programmatic Policy Extraction by Iterative Local Search Rasmus Larsen Mikkel N. Schmidt 13 0 0 18 Jan 2022
Summarising and Comparing Agent Dynamics with Contrastive Spatiotemporal Abstraction Tom Bewley J. Lawry Arthur G. Richards 27 3 0 17 Jan 2022
Verified Probabilistic Policies for Deep Reinforcement Learning E. Bacci David Parker 24 4 0 10 Jan 2022
A Survey on Interpretable Reinforcement Learning Claire Glanois Paul Weng Matthieu Zimmer Dong Li Tianpei Yang Jianye Hao Wulong Liu OffRL 23 95 0 24 Dec 2021
Programming with Neural Surrogates of Programs Alex Renda Yi Ding Michael Carbin 24 2 0 12 Dec 2021
Temporal-Spatial Causal Interpretations for Vision-Based Reinforcement Learning Wenjie Shi Gao Huang Shiji Song Cheng Wu 34 9 0 06 Dec 2021