A Lyapunov-based Approach to Safe Reinforcement Learning

20 May 2018

Yinlam Chow

Ofir Nachum

Edgar A. Duénez-Guzmán

Mohammad Ghavamzadeh

ArXiv PDF HTML

Papers citing "A Lyapunov-based Approach to Safe Reinforcement Learning"

50 / 286 papers shown

Title
Enhancing LLM Safety via Constrained Direct Preference Optimization Zixuan Liu Xiaolin Sun Zizhan Zheng 48 20 0 04 Mar 2024
Safe Hybrid-Action Reinforcement Learning-Based Decision and Control for Discretionary Lane Change Ruichen Xu Xiao Liu Jinming Xu Yuan Lin 28 1 0 01 Mar 2024
Concurrent Learning of Policy and Unknown Safety Constraints in Reinforcement Learning Lunet Yifru Ali Baheri OffRL 41 1 0 24 Feb 2024
Reinforcement Learning with Elastic Time Steps Dong Wang Giovanni Beltrame 22 2 0 22 Feb 2024
Safety Filters for Black-Box Dynamical Systems by Learning Discriminating Hyperplanes Will Lavanakul Jason J. Choi Koushil Sreenath Claire J. Tomlin 57 14 0 07 Feb 2024
Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation Paul Daoudi Mathias Formoso Othman Gaizi Achraf Azize Evrard Garcelon OffRL 28 0 0 24 Dec 2023
Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis Rohan Mitta Hosein Hasanbeig Jun Wang Daniel Kroening Y. Kantaros Alessandro Abate 18 1 0 18 Dec 2023
Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming Minjae Cho Chuangchuang Sun 35 3 0 15 Dec 2023
Modeling Risk in Reinforcement Learning: A Literature Mapping Leonardo Villalobos-Arias Derek Martin Abhijeet Krishnan Madeleine Gagné Colin M. Potts Arnav Jhala 28 0 0 08 Dec 2023
Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees Dorde Zikelic Mathias Lechner Abhinav Verma K. Chatterjee T. Henzinger 40 10 0 03 Dec 2023
Efficient Off-Policy Safe Reinforcement Learning Using Trust Region Conditional Value at Risk Dohyeong Kim Songhwai Oh OffRL 29 19 0 01 Dec 2023
A safe exploration approach to constrained Markov decision processes Tingting Ni Maryam Kamgarpour 49 3 0 01 Dec 2023
Deep Reinforcement Learning Graphs: Feedback Motion Planning via Neural Lyapunov Verification A. Ghanbarzadeh Esmaeil Najafi 19 0 0 29 Nov 2023
Efficient Open-world Reinforcement Learning via Knowledge Distillation and Autonomous Rule Discovery Ekaterina Nikonova Cheng Xue Jochen Renz CLL 28 1 0 24 Nov 2023
Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning F. D. Lellis M. Coraggio G. Russo Mirco Musolesi Mario di Bernardo OffRL 35 4 0 16 Nov 2023
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization Siqi Shen Chennan Ma Chao Li Weiquan Liu Yongquan Fu Songzhu Mei Xinwang Liu Cheng-Yu Wang 23 10 0 03 Nov 2023
SCPO: Safe Reinforcement Learning with Safety Critic Policy Optimization Jaafar Mhamed Shangding Gu 29 0 0 01 Nov 2023
DePAint: A Decentralized Safe Multi-Agent Reinforcement Learning Algorithm considering Peak and Average Constraints Raheeb Hassan K. M. S. Wadith Md. Mamun-or Rashid Md. Mosaddek Khan 32 2 0 22 Oct 2023
Reduced Policy Optimization for Continuous Control with Hard Constraints Shutong Ding Jingya Wang Yali Du Ye-ling Shi 22 5 0 14 Oct 2023
Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization Fan Yang Wen-Min Zhou Zuxin Liu Ding Zhao David Held 25 1 0 10 Oct 2023
Confronting Reward Model Overoptimization with Constrained RLHF Ted Moskovitz Aaditya K. Singh DJ Strouse T. Sandholm Ruslan Salakhutdinov Anca D. Dragan Stephen Marcus McAleer 50 48 0 06 Oct 2023
Safe Reinforcement Learning via Hierarchical Adaptive Chance-Constraint Safeguards Zhaorun Chen Zhuokai Zhao Tairan He Binhao Chen Xuhao Zhao Liang Gong Chengliang Liu 29 3 0 05 Oct 2023
Distributionally Safe Reinforcement Learning under Model Uncertainty: A Single-Level Approach by Differentiable Convex Programming A. Chriat Chuangchuang Sun 30 1 0 03 Oct 2023
Provably Efficient Exploration in Constrained Reinforcement Learning:Posterior Sampling Is All You Need Danil Provodin Pratik Gajane Mykola Pechenizkiy M. Kaptein 39 0 0 27 Sep 2023
MoDem-V2: Visuo-Motor World Models for Real-World Robot Manipulation Patrick E. Lancaster Nicklas Hansen Aravind Rajeswaran Vikash Kumar LM&Ro 33 14 0 25 Sep 2023
Learning Adaptive Safety for Multi-Agent Systems Luigi Berducci Shuo Yang Rahul Mangharam Radu Grosu 46 4 0 19 Sep 2023
Shielded Reinforcement Learning for Hybrid Systems Asger Horn Brorholt P. G. Jensen Kim G. Larsen Florian Lorber Christian Schilling 23 4 0 28 Aug 2023
Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion Simon Guist Jan Schneider Hao Ma Tianyu Cui V. Berenz ... Felix Gruninger M. Muhlebach J. Fiene Bernhard Schölkopf Le Chen 52 4 0 05 Jul 2023
Is Risk-Sensitive Reinforcement Learning Properly Resolved? Ruiwen Zhou Minghuan Liu Kan Ren Xufang Luo Weinan Zhang Dongsheng Li 27 2 0 02 Jul 2023
Value Functions are Control Barrier Functions: Verification of Safe Policies using Control Theory Daniel C.H. Tan Fernando Acero Robert McCarthy Dimitrios Kanoulas Zhibin Li OffRL 42 3 0 06 Jun 2023
Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces Brahma S. Pavse M. Zurek Yudong Chen Qiaomin Xie Josiah P. Hanna OffRL 46 1 0 02 Jun 2023
Identifiability and Generalizability in Constrained Inverse Reinforcement Learning Andreas Schlaginhaufen Maryam Kamgarpour 29 10 0 01 Jun 2023
ROSARL: Reward-Only Safe Reinforcement Learning Geraud Nangue Tasse Tamlin Love Mark W. Nemecek Steven D. James Benjamin Rosman 29 3 0 31 May 2023
Emergent Incident Response for Unmanned Warehouses with Multi-agent Systems* Yibo Guo Mingxin Li Jingting Zong Mingliang Xu 26 0 0 29 May 2023
Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions Desong Du Shao-Fu Han Naiming Qi Haitham Bou-Ammar Jun Wang Wei Pan 42 15 0 16 May 2023
On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approach A. Chriat Chuangchuang Sun 29 4 0 05 May 2023
Joint Learning of Policy with Unknown Temporal Constraints for Safe Reinforcement Learning Lunet Yifru Ali Baheri 17 1 0 30 Apr 2023
Model-based Dynamic Shielding for Safe and Efficient Multi-Agent Reinforcement Learning Wenli Xiao Yiwei Lyu John M. Dolan 24 7 0 13 Apr 2023
Stable and Safe Reinforcement Learning via a Barrier-Lyapunov Actor-Critic Approach Liqun Zhao Konstantinos Gatsis A. Papachristodoulou 36 13 0 08 Apr 2023
Neural Operators of Backstepping Controller and Observer Gain Functions for Reaction-Diffusion PDEs Miroslav Krstic Luke Bhan Yuanyuan Shi 56 28 0 18 Mar 2023
Learning Stabilization Control from Observations by Learning Lyapunov-like Proxy Models Milan Ganai Chiaki Hirayama Ya-Chien Chang Sicun Gao 37 6 0 03 Mar 2023
Efficient Exploration Using Extra Safety Budget in Constrained Policy Optimization Haotian Xu Shengjie Wang Zhaolei Wang Yunzhe Zhang Qing Zhuo Yang Gao Tao Zhang 18 0 0 28 Feb 2023
A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors Shangding Gu Alap Kshirsagar Yali Du Guang Chen Jan Peters Alois C. Knoll 39 14 0 25 Feb 2023
Constrained Reinforcement Learning using Distributional Representation for Trustworthy Quadrotor UAV Tracking Control Yanran Wang David E. Boyle 33 8 0 22 Feb 2023
Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning Yu Lu Arunesh Sinha Pradeep Varakantham 28 0 0 21 Feb 2023
Safe Deep Reinforcement Learning by Verifying Task-Level Properties Enrico Marchesini Luca Marzari Alessandro Farinelli Chris Amato OffRL 28 13 0 20 Feb 2023
EnergyShield: Provably-Safe Offloading of Neural Network Controllers for Energy Efficiency Mohanad Odema James Ferlez Goli Vaisi Yasser Shoukry M. A. Al Faruque 33 3 0 13 Feb 2023
Provably Safe Reinforcement Learning with Step-wise Violation Constraints Nuoya Xiong Yihan Du Longbo Huang 28 9 0 13 Feb 2023
Adaptive Aggregation for Safety-Critical Control Huiliang Zhang Di Wu Benoit Boulet 31 0 0 07 Feb 2023
State-wise Safe Reinforcement Learning: A Survey Weiye Zhao Tairan He Rui Chen Tianhao Wei Changliu Liu 39 60 0 06 Feb 2023