An Inductive Synthesis Framework for Verifiable Reinforcement Learning

An Inductive Synthesis Framework for Verifiable Reinforcement Learning

16 July 2019

Suresh Jagannathan

Papers citing "An Inductive Synthesis Framework for Verifiable Reinforcement Learning"

19 / 19 papers shown

Title
Inductive Generalization in Reinforcement Learning from Specifications Vignesh Subramanian Rohit Kushwah Subhajit Roy Suguman Bansal OffRL 41 0 0 05 Jun 2024
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 55 4 0 26 May 2024
Probabilistic Model Checking of Stochastic Reinforcement Learning Policies Dennis Gross Helge Spieker OffRL 32 2 0 27 Mar 2024
Guiding Safe Exploration with Weakest Preconditions Greg Anderson Swarat Chaudhuri Işıl Dillig 40 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
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
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
Programmatic Reward Design by Example Weichao Zhou Wenchao Li 34 15 0 14 Dec 2021
A Survey on AI Assurance Feras A. Batarseh Laura J. Freeman 31 65 0 15 Nov 2021
Learning Density Distribution of Reachable States for Autonomous Systems Yue Meng Dawei Sun Zeng Qiu Md Tawhid Bin Waez Chuchu Fan 82 19 0 14 Sep 2021
Learning to Synthesize Programs as Interpretable and Generalizable Policies Dweep Trivedi Jesse Zhang Shao-Hua Sun Joseph J. Lim NAI 24 72 0 31 Aug 2021
Self-Correcting Neural Networks For Safe Classification Klas Leino Aymeric Fromherz Ravi Mangal Matt Fredrikson Bryan Parno C. Păsăreanu 32 4 0 23 Jul 2021
Scalable Synthesis of Verified Controllers in Deep Reinforcement Learning Zikang Xiong Suresh Jagannathan 32 6 0 20 Apr 2021
NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems Hoang-Dung Tran Xiaodong Yang Diego Manzanas Lopez Patrick Musau L. V. Nguyen Weiming Xiang Stanley Bak Taylor T. Johnson 34 239 0 12 Apr 2020
ART: Abstraction Refinement-Guided Training for Provably Correct Neural Networks Xuankang Lin He Zhu R. Samanta Suresh Jagannathan AAML 27 28 0 17 Jul 2019
MoËT: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning Marko Vasic Andrija Petrović Kaiyuan Wang Mladen Nikolic Rishabh Singh S. Khurshid OffRL MoE 20 23 0 16 Jun 2019
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 251 1,842 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 933 0 21 Oct 2016
Safe Exploration in Markov Decision Processes T. Moldovan Pieter Abbeel 78 308 0 22 May 2012