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Exploration

86 papers

Papers per year

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Papers

On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game ICML 2021
Non-decreasing Quantile Function Network with Efficient Exploration for Distributional Reinforcement Learning IJCAI 2021
Adaptive Probing Policies for Shortest Path Routing NIPS 2020
Reinforcement Learning with Non-Markovian Rewards AAAI 2020
Beliefs We Can Believe in: Replacing Assumptions with Data in Real-Time Search AAAI 2020
Novel Is Not Always Better: On the Relation between Novelty and Dominance Pruning AAAI 2020
Active Vision for Early Recognition of Human Actions CVPR 2020
Reward-Free Exploration for Reinforcement Learning ICML 2020
Efficient Pure Exploration in Adaptive Round model NIPS 2019
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning NIPS 2019
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle NIPS 2019
Worst-Case Regret Bounds for Exploration via Randomized Value Functions NIPS 2019
Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards NIPS 2019
Better Exploration with Optimistic Actor Critic NIPS 2019
Learning Transferable Graph Exploration NIPS 2019
MAVEN: Multi-Agent Variational Exploration NIPS 2019
Model Learning for Look-Ahead Exploration in Continuous Control AAAI 2019
Diverse Exploration via Conjugate Policies for Policy Gradient Methods AAAI 2019
QUOTA: The Quantile Option Architecture for Reinforcement Learning AAAI 2019
Dead-ends and Secure Exploration in Reinforcement Learning ICML 2019
Meta-Reinforcement Learning of Structured Exploration Strategies NIPS 2018
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling NIPS 2018
A Bandit Approach to Sequential Experimental Design with False Discovery Control NIPS 2018
Exploration in Structured Reinforcement Learning NIPS 2018
Context-dependent upper-confidence bounds for directed exploration NIPS 2018