Value Iteration
383 papers
Papers per year
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22
37
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Papers
CRSRL: Customer Routing System Using Reinforcement Learning
IJCAI 2019
DHER: Hindsight Experience Replay for Dynamic Goals
ICLR 2019
Explicit Planning for Efficient Exploration in Reinforcement Learning
NeurIPS 2019
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization
NeurIPS 2019
Hill Climbing on Value Estimates for Search-control in Dyna
IJCAI 2019
How to Combine Tree-Search Methods in Reinforcement Learning
AAAI 2019
Mapping State Space using Landmarks for Universal Goal Reaching
NeurIPS 2019
Measurement Maximizing Adaptive Sampling with Risk Bounding Functions
AAAI 2019
Measuring Structural Similarities in Finite MDPs
IJCAI 2019
Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift
AAAI 2019
Perception-Aware Point-Based Value Iteration for Partially Observable Markov Decision Processes
IJCAI 2019
Planning in entropy-regularized Markov decision processes and games
NeurIPS 2019
Planning with Expectation Models
IJCAI 2019
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces
NeurIPS 2019
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
ICML 2019
Reachable Space Characterization of Markov Decision Processes with Time Variability
RSS 2019
Sampling Networks and Aggregate Simulation for Online POMDP Planning
NeurIPS 2019
Scale-free adaptive planning for deterministic dynamics & discounted rewards
ICML 2019
Separating value functions across time-scales
ICML 2019
Sequential Patient Recruitment and Allocation for Adaptive Clinical Trials
AISTATS 2019
State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning
AAAI 2019
Successor Features Based Multi-Agent RL for Event-Based Decentralized MDPs
AAAI 2019
Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning
AISTATS 2019
The Value Function Polytope in Reinforcement Learning
ICML 2019
Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies
NeurIPS 2019