Learning Finite State Representations of Recurrent Policy Networks

29 November 2018

Papers citing "Learning Finite State Representations of Recurrent Policy Networks"

14 / 14 papers shown

Title
Policy-to-Language: Train LLMs to Explain Decisions with Flow-Matching Generated Rewards Xinyi Yang Liang Zeng Heng Dong C. Yu X. Wu H. Yang Yu Wang Milind Tambe Tonghan Wang 68 2 0 18 Feb 2025
Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search Max Liu Chan-Hung Yu Wei-Hsu Lee Cheng-Wei Hung Yen-Chun Chen Shao-Hua Sun 53 4 0 26 May 2024
Synthesizing Programmatic Policies with Actor-Critic Algorithms and ReLU Networks S. Orfanos Levi H. S. Lelis 11 6 0 04 Aug 2023
SoK: Explainable Machine Learning for Computer Security Applications A. Nadeem D. Vos Clinton Cao Luca Pajola Simon Dieck Robert Baumgartner S. Verwer 29 40 0 22 Aug 2022
Identifying Reasoning Flaws in Planning-Based RL Using Tree Explanations Kin-Ho Lam Zhengxian Lin Jed Irvine Jonathan Dodge Zeyad Shureih Roli Khanna Minsuk Kahng Alan Fern 8 7 0 28 Sep 2021
Longitudinal Distance: Towards Accountable Instance Attribution Rosina O. Weber Prateek Goel S. Amiri G. Simpson 11 0 0 23 Aug 2021
Explainable Autonomous Robots: A Survey and Perspective Tatsuya Sakai Takayuki Nagai 20 67 0 06 May 2021
Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods Nicholay Topin Stephanie Milani Fei Fang Manuela Veloso OffRL 13 32 0 25 Feb 2021
Meta-trained agents implement Bayes-optimal agents Vladimir Mikulik Grégoire Delétang Tom McGrath Tim Genewein Miljan Martic Shane Legg Pedro A. Ortega OOD FedML 27 40 0 21 Oct 2020
Re-understanding Finite-State Representations of Recurrent Policy Networks Mohamad H. Danesh Anurag Koul Alan Fern Saeed Khorram 20 20 0 06 Jun 2020
The Emerging Landscape of Explainable AI Planning and Decision Making Tathagata Chakraborti S. Sreedharan S. Kambhampati 25 112 0 26 Feb 2020
The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence G. Marcus VLM 24 353 0 14 Feb 2020
Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and Limitations Pedro Sequeira Melinda Gervasio 13 102 0 19 Dec 2019
Learning Causal State Representations of Partially Observable Environments Amy Zhang Zachary Chase Lipton Luis Villaseñor-Pineda Kamyar Azizzadenesheli Anima Anandkumar Laurent Itti Joelle Pineau Tommaso Furlanello CML 21 49 0 25 Jun 2019