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Reinforcement Learning

2932 directly classified papers

Papers per year

Papers

Determinantal Reinforcement Learning AAAI 2019
Efficient Counterfactual Learning from Bandit Feedback AAAI 2019
Explicit Explore-Exploit Algorithms in Continuous State Spaces NIPS 2019
Robust exploration in linear quadratic reinforcement learning NIPS 2019
State Aggregation Learning from Markov Transition Data NIPS 2019
Adaptive Auxiliary Task Weighting for Reinforcement Learning NIPS 2019
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs NIPS 2019
Discovery of Useful Questions as Auxiliary Tasks NIPS 2019
Learning Local Search Heuristics for Boolean Satisfiability NIPS 2019
Learning to Perform Local Rewriting for Combinatorial Optimization NIPS 2019
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment NIPS 2019
RUDDER: Return Decomposition for Delayed Rewards NIPS 2019
Hindsight Credit Assignment NIPS 2019
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning NIPS 2019
When to use parametric models in reinforcement learning? NIPS 2019
Policy Continuation with Hindsight Inverse Dynamics NIPS 2019
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle NIPS 2019
A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning NIPS 2019
Information-Theoretic Confidence Bounds for Reinforcement Learning NIPS 2019
On the Correctness and Sample Complexity of Inverse Reinforcement Learning NIPS 2019
Provably Efficient Q-Learning with Low Switching Cost NIPS 2019
Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm NIPS 2019
Budgeted Reinforcement Learning in Continuous State Space NIPS 2019
Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling NIPS 2019
Planning in entropy-regularized Markov decision processes and games NIPS 2019