exploration bonus

Data-Efficient Reinforcement Learning for Malaria Control IJCAI 2021 Dynamic Bottleneck for Robust Self-Supervised Exploration NeurIPS 2021 Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning ICML 2021 Fast active learning for pure exploration in reinforcement learning ICML 2021 From Optimality to Robustness: Adaptive Re-Sampling Strategies in Stochastic Bandits NeurIPS 2021 Learning and Planning for Time-Varying MDPs Using Maximum Likelihood Estimation JMLR 2021 On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game ICML 2021 Randomized Exploration in Reinforcement Learning with General Value Function Approximation ICML 2021 Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret NeurIPS 2021 Count-Based Exploration with the Successor Representation AAAI 2020 Flow-based Intrinsic Curiosity Module IJCAI 2020 IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL IJCAI 2020 On Bonus Based Exploration Methods In The Arcade Learning Environment ICLR 2020 Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP ICLR 2020 Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes NeurIPS 2020 Curiosity-Bottleneck: Exploration By Distilling Task-Specific Novelty ICML 2019 Distributional Reinforcement Learning for Efficient Exploration ICML 2019 Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs NeurIPS 2019 Count-Based Exploration with Neural Density Models ICML 2017 #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning NeurIPS 2017 Minimax Regret Bounds for Reinforcement Learning ICML 2017 Unifying Count-Based Exploration and Intrinsic Motivation NeurIPS 2016 VIME: Variational Information Maximizing Exploration NeurIPS 2016 Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress NeurIPS 2012