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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 901–925 of 1918 papers

TitleStatusHype
Inverse Policy Evaluation for Value-based Sequential Decision-making—0
Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration—0
Deep reinforcement learning with a particle dynamics environment applied to emergency evacuation of a room with obstacles—0
Investigating Reinforcement Learning Agents for Continuous State Space Environments—0
Investigating the Edge of Stability Phenomenon in Reinforcement Learning—0
Decentralized Microgrid Energy Management: A Multi-agent Correlated Q-learning Approach—0
Investigating the Properties of Neural Network Representations in Reinforcement Learning—0
Decentralized model-free reinforcement learning in stochastic games with average-reward objective—0
IoT-Aerial Base Station Task Offloading with Risk-Sensitive Reinforcement Learning for Smart Agriculture—0
Autonomous Vehicle Decision-Making Framework for Considering Malicious Behavior at Unsignalized Intersections—0
IQL-TD-MPC: Implicit Q-Learning for Hierarchical Model Predictive Control—0
Decentralized Multi-Robot Formation Control Using Reinforcement Learning—0
Is Q-learning an Ill-posed Problem?—0
Algorithmic Trading with Fitted Q Iteration and Heston Model—0
Autonomous Penetration Testing using Reinforcement Learning—0
Is Risk-Sensitive Reinforcement Learning Properly Resolved?—0
"Jam Me If You Can'': Defeating Jammer with Deep Dueling Neural Network Architecture and Ambient Backscattering Augmented Communications—0
Decentralized Semantic Traffic Control in AVs Using RL and DQN for Dynamic Roadblocks—0
Joint Inference of Reward Machines and Policies for Reinforcement Learning—0
Joint Learning of Interactive Spoken Content Retrieval and Trainable User Simulator—0
Joint Learning of Reward Machines and Policies in Environments with Partially Known Semantics—0
Decision-making at Unsignalized Intersection for Autonomous Vehicles: Left-turn Maneuver with Deep Reinforcement Learning—0
Joint User Association, Interference Cancellation and Power Control for Multi-IRS Assisted UAV Communications—0
KAN v.s. MLP for Offline Reinforcement Learning—0
Deep Reinforcement Learning with Adjustments—0
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