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Q-Learning

The goal of Q-learning is to learn a policy, which tells an agent what action to take under what circumstances.

( Image credit: Playing Atari with Deep Reinforcement Learning )

Papers

Showing 16011650 of 1918 papers

TitleStatusHype
Stochastic approximation with cone-contractive operators: Sharp _-bounds for Q-learningCode0
Reinforcement Learning for Robotics and Control with Active Uncertainty Reduction0
Design of Artificial Intelligence Agents for Games using Deep Reinforcement Learning0
Domain Adversarial Reinforcement Learning for Partial Domain Adaptation0
A Reinforcement Learning Perspective on the Optimal Control of Mutation Probabilities for the (1+1) Evolutionary Algorithm: First Results on the OneMax Problem0
Pretrain Soft Q-Learning with Imperfect Demonstrations0
Toward Packet Routing with Fully-distributed Multi-agent Deep Reinforcement Learning0
Accelerated Target Updates for Q-learning0
Deep Ordinal Reinforcement LearningCode0
Comprehensible Context-driven Text Game PlayingCode0
Efficient Model-free Reinforcement Learning in Metric SpacesCode0
Soft Q-Learning with Mutual-Information Regularization0
Learning agents with prioritization and parameter noise in continuous state and action space0
Two-Timescale Networks for Nonlinear Value Function Approximation0
A Deep Q-Learning Method for Downlink Power Allocation in Multi-Cell Networks0
Zap Q-Learning for Optimal Stopping Time Problems0
Target-Based Temporal Difference Learning0
Stochastic Lipschitz Q-Learning0
Deep Q-Learning for Nash Equilibria: Nash-DQNCode0
Driving Decision and Control for Autonomous Lane Change based on Deep Reinforcement Learning0
Deep Q Learning Driven CT Pancreas Segmentation with Geometry-Aware U-Net0
"Jam Me If You Can'': Defeating Jammer with Deep Dueling Neural Network Architecture and Ambient Backscattering Augmented Communications0
Patchwork: A Patch-wise Attention Network for Efficient Object Detection and Segmentation in Video Streams0
Personalized Cancer Chemotherapy Schedule: a numerical comparison of performance and robustness in model-based and model-free scheduling methodologies0
Learning Automata Based Q-learning for Content Placement in Cooperative Caching0
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI gamesCode0
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies0
Towards Characterizing Divergence in Deep Q-Learning0
Online Antenna Tuning in Heterogeneous Cellular Networks with Deep Reinforcement Learning0
Reinforcement Learning with Dynamic Boltzmann Softmax UpdatesCode0
Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces0
Deep Recurrent Q-Learning vs Deep Q-Learning on a simple Partially Observable Markov Decision Process with MinecraftCode0
Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal ControlCode0
Successive Over Relaxation Q-Learning0
Learning Heuristics over Large Graphs via Deep Reinforcement LearningCode0
Distributed Edge Caching via Reinforcement Learning in Fog Radio Access Networks0
Unifying Ensemble Methods for Q-learning via Social Choice Theory0
Diagnosing Bottlenecks in Deep Q-learning AlgorithmsCode0
Optimal and Fast Real-time Resources Slicing with Deep Dueling Neural Networks0
Distributionally Robust Reinforcement Learning0
Autonomous Airline Revenue Management: A Deep Reinforcement Learning Approach to Seat Inventory Control and Overbooking0
Heuristics, Answer Set Programming and Markov Decision Process for Solving a Set of Spatial PuzzlesCode0
Long and Short Memory Balancing in Visual Co-Tracking using Q-Learning0
Sample-Optimal Parametric Q-Learning Using Linearly Additive Features0
Learning Best Response Strategies for Agents in Ad Exchanges0
Dynamic-Weighted Simplex Strategy for Learning Enabled Cyber Physical SystemsCode0
Finite-Sample Analysis for SARSA with Linear Function Approximation0
A Theory of Regularized Markov Decision Processes0
Privacy-preserving Q-Learning with Functional Noise in Continuous State SpacesCode0
Making Deep Q-learning methods robust to time discretizationCode0
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