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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 1351–1375 of 1918 papers

TitleStatusHype
Fitted Q-Learning for Relational Domains—0
Model-Free Algorithm and Regret Analysis for MDPs with Long-Term Constraints—0
Multi-Agent Reinforcement Learning in a Realistic Limit Order Book Market Simulation—0
Reinforcement Learning-Based Joint Self-Optimisation Method for the Fuzzy Logic Handover Algorithm in 5G HetNets—0
Balancing a CartPole System with Reinforcement Learning -- A Tutorial—0
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory—0
A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret—0
A Multi-step and Resilient Predictive Q-learning Algorithm for IoT with Human Operators in the Loop: A Case Study in Water Supply Networks—0
Logical Team Q-learning: An approach towards factored policies in cooperative MARL—0
A Novel Update Mechanism for Q-Networks Based On Extreme Learning MachinesCode0
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction—0
Hyperparameter optimization with REINFORCE and Transformers—0
Mitigating Bias in Face Recognition Using Skewness-Aware Reinforcement Learning—0
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization—0
Learning-Based Joint User-AP Association and Resource Allocation in Ultra Dense Network—0
Active Measure Reinforcement Learning for Observation Cost Minimization—0
Should artificial agents ask for help in human-robot collaborative problem-solving?—0
Deep Reinforcement Learning Based Power Allocation for D2D Network—0
A reinforcement learning based decision support system in textile manufacturing process—0
Safe Learning for Near Optimal Scheduling—0
Basal Glucose Control in Type 1 Diabetes using Deep Reinforcement Learning: An In Silico Validation—0
Entropy-Augmented Entropy-Regularized Reinforcement Learning and a Continuous Path from Policy Gradient to Q-Learning—0
A Deep Q-learning/genetic Algorithms Based Novel Methodology For Optimizing Covid-19 Pandemic Government Actions—0
A Deep Reinforcement Learning Approach to Efficient Drone Mobility Support—0
An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning—0
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