conftrace_

risk-sensitive reinforcement learning

27 papers

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Also known as

RSRL

Co-occurring keywords

regret bound (1926) markov decision process (790) distributional reinforcement learning (72) conditional value at risk (50) entropic risk measure (9) policy gradient (520) policy optimization (657) deep reinforcement learning (903) value at risk (9) risk-sensitive learning (7)

Papers

Risk-Sensitive Exponential Actor Critic AAAI 2026
Optimizing Return Distributions with Distributional Dynamic Programming JMLR 2025
Learning Diverse Risk Preferences in Population-Based Self-Play AAAI 2024
SafeAR: Safe Algorithmic Recourse by Risk-Aware Policies AAAI 2024
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds JMLR 2024
Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures AISTATS 2024
A Tighter Problem-Dependent Regret Bound for Risk-Sensitive Reinforcement Learning AISTATS 2023
Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR ICML 2023
Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents ICML 2023
On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures ICML 2023
Non-stationary Risk-Sensitive Reinforcement Learning: Near-Optimal Dynamic Regret, Adaptive Detection, and Separation Design AAAI 2023
A Risk-Sensitive Approach to Policy Optimization AAAI 2023
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization NIPS 2023
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning NIPS 2023
A policy gradient approach for optimization of smooth risk measures UAI 2023
On the limitations of Markovian rewards to express multi-objective, risk-sensitive, and modal tasks UAI 2023
Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning ICML 2022
Regret Bounds for Risk-Sensitive Reinforcement Learning NIPS 2022
Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case AISTATS 2021
Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach ICML 2021
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning NIPS 2021
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret NIPS 2020
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy AAAI 2020
Stochastically Dominant Distributional Reinforcement Learning ICML 2020
State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning AAAI 2019