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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 576–600 of 1918 papers

TitleStatusHype
On Practical Robust Reinforcement Learning: Practical Uncertainty Set and Double-Agent Algorithm—0
Deep Q-Learning-based Distribution Network Reconfiguration for Reliability Improvement—0
Mixed-Integer Optimal Control via Reinforcement Learning: A Case Study on Hybrid Electric Vehicle Energy ManagementCode0
Model-free Motion Planning of Autonomous Agents for Complex Tasks in Partially Observable EnvironmentsCode0
BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading—0
Safe Q-learning for continuous-time linear systems—0
Adaptive Services Function Chain Orchestration For Digital Health Twin Use Cases: Heuristic-boosted Q-Learning Approach—0
Learned Collusion—0
IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion PoliciesCode1
Deep-Q Learning with Hybrid Quantum Neural Network on Solving Maze ProblemsCode0
Graph Exploration for Effective Multi-agent Q-Learning—0
Quantum deep Q learning with distributed prioritized experience replay—0
A study on a Q-Learning algorithm application to a manufacturing assembly problem—0
Collaborative Multi-BS Power Management for Dense Radio Access Network using Deep Reinforcement LearningCode0
Exploring the Noise Resilience of Successor Features and Predecessor Features Algorithms in One and Two-Dimensional Environments—0
Deep reinforcement learning applied to an assembly sequence planning problem with user preferences—0
RELS-DQN: A Robust and Efficient Local Search Framework for Combinatorial Optimization—0
Reinforcement Learning Based Minimum State-flipped Control for the Reachability of Boolean Control Networks—0
Automaton-Guided Curriculum Generation for Reinforcement Learning AgentsCode0
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural NetworksCode0
Full Gradient Deep Reinforcement Learning for Average-Reward Criterion—0
Deep Reinforcement Learning Based Optimal Infinite-Horizon Control of Probabilistic Boolean Control Networks—0
Quantitative Trading using Deep Q Learning—0
A Tutorial Introduction to Reinforcement Learning—0
Understanding Reinforcement Learning Algorithms: The Progress from Basic Q-learning to Proximal Policy Optimization—0
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