{"total":59,"rows":[{"id":"2205.10330","title":"A Review of Safe Reinforcement Learning: Methods, Theory and Applications","created":"2022-05-20","cited_by_count":181,"area":null},{"id":"2202.06558","title":"Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation","created":"2022-02-14","cited_by_count":69,"area":null},{"id":"2107.02729","title":"AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning","created":"2021-07-06","cited_by_count":48,"area":null},{"id":"2205.05138","title":"Efficient Risk-Averse Reinforcement Learning","created":"2022-05-10","cited_by_count":43,"area":null},{"id":"2206.04436","title":"Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk","created":"2022-06-09","cited_by_count":41,"area":null},{"id":"2209.08025","title":"Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability","created":"2022-09-16","cited_by_count":36,"area":null},{"id":"2101.00531","title":"Context-Aware Safe Reinforcement Learning for Non-Stationary Environments","created":"2021-01-02","cited_by_count":33,"area":null},{"id":"2302.03201","title":"Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR","created":"2023-02-07","cited_by_count":32,"area":null},{"id":"2102.05762","title":"Risk-Averse Bayes-Adaptive Reinforcement Learning","created":"2021-02-10","cited_by_count":29,"area":null},{"id":"2210.05650","title":"Regret Bounds for Risk-Sensitive Reinforcement Learning","created":"2022-10-11","cited_by_count":26,"area":null},{"id":"2206.02678","title":"Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path","created":"2022-06-06","cited_by_count":22,"area":null},{"id":"2103.02827","title":"On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk","created":"2021-03-04","cited_by_count":20,"area":null},{"id":"2202.07013","title":"Robust Policy Learning over Multiple Uncertainty Sets","created":"2022-02-14","cited_by_count":18,"area":null},{"id":"2112.08746","title":"Unsupervised Reinforcement Learning in Multiple Environments","created":"2021-12-16","cited_by_count":17,"area":null},{"id":"2102.11075","title":"SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement Learning","created":"2021-02-22","cited_by_count":15,"area":null},{"id":"2103.09230","title":"Lyapunov Barrier Policy Optimization","created":"2021-03-16","cited_by_count":12,"area":null},{"id":"2107.11722","title":"Learning Risk-aware Costmaps for Traversability in Challenging Environments","created":"2021-07-25","cited_by_count":12,"area":null},{"id":"2205.12184","title":"Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning","created":"2022-05-24","cited_by_count":12,"area":null},{"id":"2301.11147","title":"Train Hard, Fight Easy: Robust Meta Reinforcement Learning","created":"2023-01-26","cited_by_count":12,"area":null},{"id":"2307.08873","title":"An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient","created":"2023-07-17","cited_by_count":12,"area":null},{"id":"2102.01985","title":"Variance Penalized On-Policy and Off-Policy Actor-Critic","created":"2021-02-03","cited_by_count":10,"area":null},{"id":"2306.01460","title":"ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages","created":"2023-06-02","cited_by_count":10,"area":null},{"id":"2105.04816","title":"Spectral risk-based learning using unbounded losses","created":"2021-05-11","cited_by_count":8,"area":null},{"id":"2111.06803","title":"Two steps to risk sensitivity","created":"2021-11-12","cited_by_count":8,"area":null},{"id":"2309.06239","title":"Risk-Aware Reinforcement Learning through Optimal Transport Theory","created":"2023-09-12","cited_by_count":8,"area":null},{"id":"2602.16796","title":"Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning","created":"2026-02-18","cited_by_count":8,"area":null},{"id":"2301.08940","title":"Quasi-optimal Reinforcement Learning with Continuous Actions","created":"2023-01-21","cited_by_count":7,"area":null},{"id":"2108.11645","title":"Robust Model-based Reinforcement Learning for Autonomous Greenhouse Control","created":"2021-08-26","cited_by_count":6,"area":null},{"id":"2212.14743","title":"Risk-Sensitive Policy with Distributional Reinforcement Learning","created":"2022-12-30","cited_by_count":6,"area":null},{"id":"2311.11965","title":"Provably Efficient CVaR RL in Low-rank MDPs","created":"2023-11-20","cited_by_count":6,"area":null},{"id":"2110.01490","title":"Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids","created":"2021-10-04","cited_by_count":5,"area":null},{"id":"2110.12746","title":"Planning for Risk-Aversion and Expected Value in MDPs","created":"2021-10-25","cited_by_count":5,"area":null},{"id":"2211.07767","title":"Learning to Optimize with Stochastic Dominance Constraints","created":"2022-11-14","cited_by_count":5,"area":null},{"id":"2301.05981","title":"Risk-Averse Reinforcement Learning via Dynamic Time-Consistent Risk Measures","created":"2023-01-14","cited_by_count":5,"area":null},{"id":"2308.13011","title":"Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory","created":"2023-08-24","cited_by_count":5,"area":null},{"id":"2211.10815","title":"Non-stationary Risk-sensitive Reinforcement Learning: Near-optimal Dynamic Regret, Adaptive Detection, and Separation Design","created":"2022-11-19","cited_by_count":4,"area":null},{"id":"2605.25632","title":"Insuring Every Action: An Authority Frontier Framework for Runtime Actuarial Control of Autonomous AI Agents","created":"2026-05-25","cited_by_count":4,"area":null},{"id":"2103.05059","title":"Bias-Corrected Peaks-Over-Threshold Estimation of the CVaR","created":"2021-03-08","cited_by_count":3,"area":null},{"id":"2108.02701","title":"Lyapunov Robust Constrained-MDPs: Soft-Constrained Robustly Stable Policy Optimization under Model Uncertainty","created":"2021-08-05","cited_by_count":3,"area":null},{"id":"2404.01200","title":"Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization","created":"2024-04-01","cited_by_count":3,"area":null},{"id":"2605.26508","title":"Foundations of a Time-Consistent Counterfactual Actuarial Runtime for Autonomous AI Agents","created":"2026-05-26","cited_by_count":3,"area":null},{"id":"2411.02558","title":"Enhancing Risk Assessment in Transformers with Loss-at-Risk Functions","created":"2024-11-04","cited_by_count":2,"area":null},{"id":"2206.07376","title":"Mean-Semivariance Policy Optimization via Risk-Averse Reinforcement Learning","created":"2022-06-15","cited_by_count":1,"area":null},{"id":"2307.00141","title":"Risk-sensitive Actor-free Policy via Convex Optimization","created":"2023-06-30","cited_by_count":1,"area":null},{"id":"2402.02698","title":"Beyond Expectations: Learning with Stochastic Dominance Made Practical","created":"2024-02-05","cited_by_count":1,"area":null},{"id":"2507.14005","title":"On the Fundamental Limitations of Dual Static CVaR Decompositions in Markov Decision Processes","created":"2025-07-18","cited_by_count":1,"area":null},{"id":"2609.08064","title":"Risk-Conditioned Fine-Tuning of Large Language Models","created":"2026-09-08","cited_by_count":1,"area":null},{"id":"2108.01295","title":"MBDP: A Model-based Approach to Achieve both Robustness and Sample Efficiency via Double Dropout Planning","created":"2021-08-03","cited_by_count":0,"area":null},{"id":"2209.11596","title":"Quantification before Selection: Active Dynamics Preference for Robust Reinforcement Learning","created":"2022-09-23","cited_by_count":0,"area":null},{"id":"2303.00672","title":"Forward-PECVaR Algorithm: Exact Evaluation for CVaR SSPs","created":"2023-03-01","cited_by_count":0,"area":null},{"id":"2405.07965","title":"Fast Computation of Superquantile-Constrained Optimization Through Implicit Scenario Reduction","created":"2024-05-13","cited_by_count":0,"area":null},{"id":"2409.16866","title":"Risk-averse learning with delayed feedback","created":"2024-09-25","cited_by_count":0,"area":null},{"id":"2602.03778","title":"Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity","created":"2026-02-03","cited_by_count":0,"area":null},{"id":"2604.15695","title":"The Price of Paranoia: Robust Risk-Sensitive Cooperation in Non-Stationary Multi-Agent Reinforcement Learning","created":"2026-04-17","cited_by_count":0,"area":null},{"id":"2605.12462","title":"Towards Affordable Energy: A Gymnasium Environment for Electric Utility Demand-Response Programs","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2605.15134","title":"Training ML Models with Predictable Failures","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2606.16326","title":"Gaming-Resistant Insurance Contracts for Autonomous AI Agents: Strategy-Proof Toll Mechanism Design","created":"2026-06-15","cited_by_count":0,"area":null},{"id":"2608.15504","title":"PERO: Efficient Robust Post-Training Foundation Models for Encrypted Traffic Classification","created":"2026-08-16","cited_by_count":0,"area":null},{"id":"2609.34840","title":"Nociception as a Control Primitive: Afferent Channels and Nociceptive Memory for Agents Deployed in One Body","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}