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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

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Showing 1251–1275 of 1918 papers

TitleStatusHype
MFC-EQ: Mean-Field Control with Envelope Q-Learning for Moving Decentralized Agents in Formation—0
Millimeter Wave Communications with an Intelligent Reflector: Performance Optimization and Distributional Reinforcement Learning—0
Mimicking Human Intuition: Cognitive Belief-Driven Q-Learning—0
Minimax Optimal Q Learning with Nearest Neighbors—0
Minimizing Age-of-Information for Fog Computing-supported Vehicular Networks with Deep Q-learning—0
Minimizing the Outage Probability in a Markov Decision Process—0
Misspecified Q-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error—0
Mitigate Bias in Face Recognition using Skewness-Aware Reinforcement Learning—0
Mitigating Bias in Face Recognition Using Skewness-Aware Reinforcement Learning—0
Mitigating Relative Over-Generalization in Multi-Agent Reinforcement Learning—0
Mixed-Precision Conjugate Gradient Solvers with RL-Driven Precision Tuning—0
Mix Q-learning for Lane Changing: A Collaborative Decision-Making Method in Multi-Agent Deep Reinforcement Learning—0
Model-aided Deep Reinforcement Learning for Sample-efficient UAV Trajectory Design in IoT Networks—0
Model-Augmented Q-learning—0
Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping—0
Model-Based Reinforcement Learning for Type 1Diabetes Blood Glucose Control—0
Model-based versus model-free feeding control and water quality monitoring for fish growth tracking in aquaculture systems—0
Provably Efficient Model-Free Algorithm for MDPs with Peak Constraints—0
Model-Free Algorithm and Regret Analysis for MDPs with Long-Term Constraints—0
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games—0
Model-Free Characterizations of the Hamilton-Jacobi-Bellman Equation and Convex Q-Learning in Continuous Time—0
Model-free Control of Chaos with Continuous Deep Q-learning—0
Model-Free Mean-Field Reinforcement Learning: Mean-Field MDP and Mean-Field Q-Learning—0
Model-free optimal controller for discrete-time Markovian jump linear systems: A Q-learning approach—0
Model-free Posterior Sampling via Learning Rate Randomization—0
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