conftrace_

optimistic exploration

34 papers

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Co-occurring keywords

regret bound (1926) reinforcement learning (4352) model-based reinforcement learning (415) upper confidence bound (197) function approximation (319) sample efficiency (472) eluder dimension (22) markov decision process (790) sample complexity (1169) deep reinforcement learning (903)

Papers

Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control NIPS 2024
Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation NIPS 2024
Mitigating Transformer Overconfidence via Lipschitz Regularization UAI 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes NIPS 2023
Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion NIPS 2023
Efficient Exploration in Continuous-time Model-based Reinforcement Learning NIPS 2023
Optimistic Exploration in Reinforcement Learning Using Symbolic Model Estimates NIPS 2023
Global Optimization with Parametric Function Approximation ICML 2023
Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling COLT 2022
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency ICML 2022
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses ICML 2022
Near-optimal Thompson sampling-based algorithms for differentially private stochastic bandits UAI 2022
A free lunch from the noise: Provable and practical exploration for representation learning UAI 2022
Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States JMLR 2022
Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation ICML 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity NIPS 2022
Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning NIPS 2022
Q-learning with Logarithmic Regret AISTATS 2021
Randomized Exploration in Reinforcement Learning with General Value Function Approximation ICML 2021
Neural Pseudo-Label Optimism for the Bank Loan Problem NIPS 2021
Principled Exploration via Optimistic Bootstrapping and Backward Induction ICML 2021
Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles CORL 2021
Strategically efficient exploration in competitive multi-agent reinforcement learning UAI 2021
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning NIPS 2020
No-regret Exploration in Contextual Reinforcement Learning UAI 2020