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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 351–400 of 1918 papers

TitleStatusHype
CAN ALTQ LEARN FASTER: EXPERIMENTS AND THEORY—0
C-Learning: Learning to Achieve Goals via Recursive Classification—0
An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems—0
Collaborative Deep Reinforcement Learning for Joint Object Search—0
A Differentiable Physics Engine for Deep Learning in Robotics—0
Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear—0
An MDP Model for Censoring in Harvesting Sensors: Optimal and Approximated Solutions—0
DASA: Delay-Adaptive Multi-Agent Stochastic Approximation—0
Combining policy gradient and Q-learning—0
Combining Q-Learning and Search with Amortized Value Estimates—0
Caching Placement and Resource Allocation for Cache-Enabling UAV NOMA Networks—0
Comparative Analysis of Multi-Agent Reinforcement Learning Policies for Crop Planning Decision Support—0
Comparative Study of Q-Learning and NeuroEvolution of Augmenting Topologies for Self Driving Agents—0
Comparing NARS and Reinforcement Learning: An Analysis of ONA and Q-Learning Algorithms—0
Cache-Aided NOMA Mobile Edge Computing: A Reinforcement Learning Approach—0
Compositional Reinforcement Learning for Discrete-Time Stochastic Control Systems—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
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
Computation Offloading for Uncertain Marine Tasks by Cooperation of UAVs and Vessels—0
Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications—0
Concentration bounds for SSP Q-learning for average cost MDPs—0
Concentration of Contractive Stochastic Approximation and Reinforcement Learning—0
Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise—0
Concept and the implementation of a tool to convert industry 4.0 environments modeled as FSM to an OpenAI Gym wrapper—0
Configuring Transmission Thresholds in IIoT Alarm Scenarios for Energy-Efficient Event Reporting—0
A Novel Resource Allocation for Anti-jamming in Cognitive-UAVs: an Active Inference Approach—0
An Efficient and Uncertainty-aware Reinforcement Learning Framework for Quality Assurance in Extrusion Additive Manufacturing—0
Consecutive Task-oriented Dialog Policy Learning—0
An Overview of Machine Learning-Enabled Optimization for Reconfigurable Intelligent Surfaces-Aided 6G Networks: From Reinforcement Learning to Large Language Models—0
Bridging the Performance Gap Between Target-Free and Target-Based Reinforcement Learning With Iterated Q-Learning—0
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation—0
Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation—0
Constrained Model-Free Reinforcement Learning for Process Optimization—0
Constraints Penalized Q-learning for Safe Offline Reinforcement Learning—0
Constructing narrative using a generative model and continuous action policies—0
Contextual Conservative Q-Learning for Offline Reinforcement Learning—0
A Penalized Shared-parameter Algorithm for Estimating Optimal Dynamic Treatment Regimens—0
Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts—0
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills—0
APF+: Boosting adaptive-potential function reinforcement learning methods with a W-shaped network for high-dimensional games—0
Continuous Deep Q-Learning in Optimal Control Problems: Normalized Advantage Functions Analysis—0
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning—0
Application of Deep Q-Network in Portfolio Management—0
Continuous-time q-Learning for Jump-Diffusion Models under Tsallis Entropy—0
Continuous-time q-learning for mean-field control problems—0
Continuous-time Risk-sensitive Reinforcement Learning via Quadratic Variation Penalty—0
An Attempt to Model Human Trust with Reinforcement Learning—0
A Deep Reinforcement Learning Approach towards Pendulum Swing-up Problem based on TF-Agents—0
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