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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 476–500 of 1918 papers

TitleStatusHype
A Fairness-Oriented Reinforcement Learning Approach for the Operation and Control of Shared Micromobility ServicesCode0
Reinforcement Learning for Online Testing of Autonomous Driving Systems: a Replication and Extension Study—0
State-Separated SARSA: A Practical Sequential Decision-Making Algorithm with Recovering Rewards—0
Neural-Kernel Conditional Mean Embeddings—0
A Reinforcement Learning Approach to Dairy Farm Battery Management using Q Learning—0
Model-free Resilient Controller Design based on Incentive Feedback Stackelberg Game and Q-learning—0
Strategizing against Q-learners: A Control-theoretical Approach—0
Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services—0
Symmetric Q-learning: Reducing Skewness of Bellman Error in Online Reinforcement Learning—0
Scalable Online Exploration via CoverabilityCode0
Finite-Time Error Analysis of Soft Q-Learning: Switching System Approach—0
Algorithmic Collusion and Price Discrimination: The Over-Usage of Data—0
Enhancing Classification Performance via Reinforcement Learning for Feature Selection—0
Belief-Enriched Pessimistic Q-Learning against Adversarial State PerturbationsCode0
SMAUG: A Sliding Multidimensional Task Window-Based MARL Framework for Adaptive Real-Time Subtask Recognition—0
QF-tuner: Breaking Tradition in Reinforcement Learning—0
SPRINQL: Sub-optimal Demonstrations driven Offline Imitation LearningCode0
Reinforcement Learning for Optimal Execution when Liquidity is Time-Varying—0
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling—0
An Index Policy Based on Sarsa and Q-learning for Heterogeneous Smart Target Tracking—0
Finite-Time Error Analysis of Online Model-Based Q-Learning with a Relaxed Sampling Model—0
Easy as ABCs: Unifying Boltzmann Q-Learning and Counterfactual Regret Minimization—0
Reinforcement learning to maximise wind turbine energy generation—0
Exploiting Estimation Bias in Clipped Double Q-Learning for Continous Control Reinforcement Learning Tasks—0
Intelligent Agricultural Management Considering N_2O Emission and Climate Variability with Uncertainties—0
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