optimistic exploration

Achieving Õ(√T) Regret in Average-Reward POMDPs with Known Observation Models AISTATS 2025 Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling ICLR 2025 Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning COLT 2025 Steering No-Regret Agents in MFGs under Model Uncertainty AISTATS 2025 Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control NeurIPS 2024 Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation NeurIPS 2024 A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes NeurIPS 2023 Efficient Exploration in Continuous-time Model-based Reinforcement Learning NeurIPS 2023 Global Optimization with Parametric Function Approximation ICML 2023 Mitigating Transformer Overconfidence via Lipschitz Regularization UAI 2023 Optimistic Exploration in Reinforcement Learning Using Symbolic Model Estimates NeurIPS 2023 Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion NeurIPS 2023 A free lunch from the noise: Provable and practical exploration for representation learning UAI 2022 Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning NeurIPS 2022 Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation ICML 2022 From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses ICML 2022 Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity NeurIPS 2022 Near-optimal Thompson sampling-based algorithms for differentially private stochastic bandits UAI 2022 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 Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States JMLR 2022 Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles CoRL 2021 Neural Pseudo-Label Optimism for the Bank Loan Problem NeurIPS 2021 Principled Exploration via Optimistic Bootstrapping and Backward Induction ICML 2021 Q-learning with Logarithmic Regret AISTATS 2021