Generation of Policy-Level Explanations for Reinforcement Learning

28 May 2019

Papers citing "Generation of Policy-Level Explanations for Reinforcement Learning"

35 / 35 papers shown

Title
Policy-to-Language: Train LLMs to Explain Decisions with Flow-Matching Generated Rewards Xinyi Yang Liang Zeng Heng Dong Chao Yu X. Wu H. Yang Yu Wang Milind Tambe Tonghan Wang 76 2 0 18 Feb 2025
Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning Zuzanna Osika J. Z. Salazar F. Oliehoek P. Murukannaiah OffRL 26 1 0 07 Nov 2024
MARLens: Understanding Multi-agent Reinforcement Learning for Traffic Signal Control via Visual Analytics Yutian Zhang Guohong Zheng Zhiyuan Liu Quan Li Haipeng Zeng 39 2 0 02 Oct 2024
ADESSE: Advice Explanations in Complex Repeated Decision-Making Environments Sören Schleibaum Lu Feng Sarit Kraus Jörg P. Müller 40 2 0 31 May 2024
Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples Hao Sun Alihan Huyuk Daniel Jarrett M. Schaar OffRL 39 6 0 11 Oct 2023
Explainable Multi-Agent Reinforcement Learning for Temporal Queries Kayla Boggess Sarit Kraus Lu Feng LRM 32 11 0 17 May 2023
Programming-by-Demonstration for Long-Horizon Robot Tasks Noah T Patton Kia Rahmani Meghana Missula Joydeep Biswas Icsil Dillig 27 10 0 04 May 2023
Programmatic Imitation Learning from Unlabeled and Noisy Demonstrations Jimmy Xin Linus Zheng Kia Rahmani Jiayi Wei Jarrett Holtz Işıl Dillig Joydeep Biswas 30 1 0 02 Mar 2023
ASQ-IT: Interactive Explanations for Reinforcement-Learning Agents Yotam Amitai Guy Avni Ofra Amir 43 3 0 24 Jan 2023
Explainable Deep Reinforcement Learning: State of the Art and Challenges G. Vouros XAI 50 76 0 24 Jan 2023
XDQN: Inherently Interpretable DQN through Mimicking Andreas Kontogiannis G. Vouros 21 0 0 08 Jan 2023
Decisions that Explain Themselves: A User-Centric Deep Reinforcement Learning Explanation System Xiaoran Wu Zihan Yan Chongjie Zhang Tongshuang Wu 14 1 0 01 Dec 2022
Explainability Via Causal Self-Talk Nicholas A. Roy Junkyung Kim Neil C. Rabinowitz CML 26 7 0 17 Nov 2022
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges Yunpeng Qing Shunyu Liu Mingli Song Huiqiong Wang Mingli Song XAI 33 1 0 12 Nov 2022
Symbolic Distillation for Learned TCP Congestion Control S. Sharan Wenqing Zheng Kuo-Feng Hsu Jiarong Xing Ang Chen Zhangyang Wang 26 5 0 24 Oct 2022
Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities Jasmina Gajcin Ivana Dusparic CML OffRL 35 8 0 21 Oct 2022
Toward Policy Explanations for Multi-Agent Reinforcement Learning Kayla Boggess Sarit Kraus Lu Feng 14 18 0 26 Apr 2022
Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning Yuansheng Xie Soroush Vosoughi Saeed Hassanpour 23 2 0 30 Mar 2022
Lazy-MDPs: Towards Interpretable Reinforcement Learning by Learning When to Act Alexis Jacq Johan Ferret Olivier Pietquin M. Geist 24 9 0 16 Mar 2022
A Survey of Explainable Reinforcement Learning Stephanie Milani Nicholay Topin Manuela Veloso Fei Fang XAI LRM 22 52 0 17 Feb 2022
Local Explanations for Reinforcement Learning Ronny Luss Amit Dhurandhar Miao Liu FAtt OffRL 8 3 0 08 Feb 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI Meike Nauta Jan Trienes Shreyasi Pathak Elisa Nguyen Michelle Peters Yasmin Schmitt Jorg Schlotterer M. V. Keulen C. Seifert ELM XAI 28 396 0 20 Jan 2022
Summarising and Comparing Agent Dynamics with Contrastive Spatiotemporal Abstraction Tom Bewley J. Lawry Arthur G. Richards 14 3 0 17 Jan 2022
A Survey on Interpretable Reinforcement Learning Claire Glanois Paul Weng Matthieu Zimmer Dong Li Tianpei Yang Jianye Hao Wulong Liu OffRL 23 94 0 24 Dec 2021
Tell me why! Explanations support learning relational and causal structure Andrew Kyle Lampinen Nicholas A. Roy Ishita Dasgupta Stephanie C. Y. Chan Allison C. Tam ... Chen Yan Adam Santoro Neil C. Rabinowitz Jane X. Wang Felix Hill 35 45 0 07 Dec 2021
Feature-Based Interpretable Reinforcement Learning based on State-Transition Models Omid Davoodi Majid Komeili FAtt OffRL 11 5 0 14 May 2021
Learning Symbolic Rules for Interpretable Deep Reinforcement Learning Zhihao Ma Yuzheng Zhuang Paul Weng Hankui Zhuo Dong Li Wulong Liu Jianye Hao NAI 51 14 0 15 Mar 2021
Iterative Program Synthesis for Adaptable Social Navigation Jarrett Holtz S. Andrews Arjun Guha Joydeep Biswas 17 8 0 08 Mar 2021
Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods Nicholay Topin Stephanie Milani Fei Fang Manuela Veloso OffRL 21 32 0 25 Feb 2021
A Bayesian Account of Measures of Interpretability in Human-AI Interaction S. Sreedharan Anagha Kulkarni Tathagata Chakraborti David E. Smith S. Kambhampati 12 10 0 22 Nov 2020
What Did You Think Would Happen? Explaining Agent Behaviour Through Intended Outcomes Herman Yau Chris Russell Simon Hadfield FAtt LRM 28 36 0 10 Nov 2020
Ranking Policy Decisions Hadrien Pouget Hana Chockler Youcheng Sun Daniel Kroening OffRL 9 6 0 31 Aug 2020
Robot Action Selection Learning via Layered Dimension Informed Program Synthesis Jarrett Holtz Arjun Guha Joydeep Biswas 17 7 0 10 Aug 2020
The Emerging Landscape of Explainable AI Planning and Decision Making Tathagata Chakraborti S. Sreedharan S. Kambhampati 27 112 0 26 Feb 2020
Model-Free Model Reconciliation S. Sreedharan Alberto Olmo Hernandez A. Mishra S. Kambhampati 12 33 0 17 Mar 2019