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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 676–700 of 1918 papers

TitleStatusHype
Computation Offloading for Uncertain Marine Tasks by Cooperation of UAVs and Vessels—0
A Novel Deep Reinforcement Learning Based Stock Direction Prediction using Knowledge Graph and Community Aware Sentiments—0
Compressive Features in Offline Reinforcement Learning for Recommender Systems—0
A Note on Target Q-learning For Solving Finite MDPs with A Generative Oracle—0
An Optimization Method-Assisted Ensemble Deep Reinforcement Learning Algorithm to Solve Unit Commitment Problems—0
A Double Q-Learning Approach for Navigation of Aerial Vehicles with Connectivity Constraint—0
Accelerated Value Iteration via Anderson Mixing—0
Compositional Reinforcement Learning for Discrete-Time Stochastic Control Systems—0
Comparing NARS and Reinforcement Learning: An Analysis of ONA and Q-Learning Algorithms—0
Comparative Study of Q-Learning and NeuroEvolution of Augmenting Topologies for Self Driving Agents—0
An Optimal Online Method of Selecting Source Policies for Reinforcement Learning—0
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms—0
Comparative Analysis of Multi-Agent Reinforcement Learning Policies for Crop Planning Decision Support—0
A Non-Asymptotic Theory of Seminorm Lyapunov Stability: From Deterministic to Stochastic Iterative Algorithms—0
Combining Q-Learning and Search with Amortized Value Estimates—0
Combining policy gradient and Q-learning—0
Anomaly Detection via Learning-Based Sequential Controlled Sensing—0
Action Q-Transformer: Visual Explanation in Deep Reinforcement Learning with Encoder-Decoder Model using Action Query—0
An MDP Model for Censoring in Harvesting Sensors: Optimal and Approximated Solutions—0
Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear—0
A Differentiable Physics Engine for Deep Learning in Robotics—0
Collaborative Deep Reinforcement Learning for Joint Object Search—0
An Index Policy Based on Sarsa and Q-learning for Heterogeneous Smart Target Tracking—0
C-Learning: Learning to Achieve Goals via Recursive Classification—0
An Independent Study of Reinforcement Learning and Autonomous Driving—0
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