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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 251–300 of 1918 papers

TitleStatusHype
Attitude Control of Highly Maneuverable Aircraft Using an Improved Q-learning—0
A Tutorial Introduction to Reinforcement Learning—0
A Hysteretic Q-learning Coordination Framework for Emerging Mobility Systems in Smart Cities—0
Adaptive Stochastic Resource Control: A Machine Learning Approach—0
Applying Reinforcement Learning to Option Pricing and Hedging—0
Active Inference in Hebbian Learning Networks—0
Causal Mean Field Multi-Agent Reinforcement Learning—0
Application of Deep Reinforcement Learning to Payment Fraud—0
Application of Deep Q-Network in Portfolio Management—0
Adversarial Agents For Attacking Inaudible Voice Activated Devices—0
Application of Deep Q Learning with Simulation Results for Elevator Optimization—0
APF+: Boosting adaptive-potential function reinforcement learning methods with a W-shaped network for high-dimensional games—0
Advancing Forest Fire Prevention: Deep Reinforcement Learning for Effective Firebreak Placement—0
Active Finite Reward Automaton Inference and Reinforcement Learning Using Queries and Counterexamples—0
A Penalized Shared-parameter Algorithm for Estimating Optimal Dynamic Treatment Regimens—0
An Initial Introduction to Cooperative Multi-Agent Reinforcement Learning—0
Advancing ECG Diagnosis Using Reinforcement Learning on Global Waveform Variations Related to P Wave and PR Interval—0
AoI Minimization in Status Update Control with Energy Harvesting Sensors—0
Anypath Routing Protocol Design via Q-Learning for Underwater Sensor Networks—0
Advancing Algorithmic Trading: A Multi-Technique Enhancement of Deep Q-Network Models—0
Accelerating Goal-Directed Reinforcement Learning by Model Characterization—0
Multi-Objective Deep Reinforcement Learning for Optimisation in Autonomous Systems—0
Censored Deep Reinforcement Patrolling with Information Criterion for Monitoring Large Water Resources using Autonomous Surface Vehicles—0
Combining policy gradient and Q-learning—0
An Overview of Machine Learning-Enabled Optimization for Reconfigurable Intelligent Surfaces-Aided 6G Networks: From Reinforcement Learning to Large Language Models—0
A Dual-Hormone Closed-Loop Delivery System for Type 1 Diabetes Using Deep Reinforcement Learning—0
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory—0
A Novel Resource Allocation for Anti-jamming in Cognitive-UAVs: an Active Inference Approach—0
A Novel Reinforcement Learning Model for Post-Incident Malware Investigations—0
Active Deep Q-learning with Demonstration—0
CAQL: Continuous Action Q-Learning—0
A Novel Multi-Objective Reinforcement Learning Algorithm for Pursuit-Evasion Game—0
A Novel Deep Reinforcement Learning Based Stock Direction Prediction using Knowledge Graph and Community Aware Sentiments—0
Accelerated Value Iteration via Anderson Mixing—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 Target Updates for Q-learning—0
Career Path Recommendations for Long-term Income Maximization: A Reinforcement Learning Approach—0
An Optimal Online Method of Selecting Source Policies for Reinforcement Learning—0
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms—0
A Non-Asymptotic Theory of Seminorm Lyapunov Stability: From Deterministic to Stochastic Iterative Algorithms—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
Action-modulated midbrain dopamine activity arises from distributed control policies—0
An MDP Model for Censoring in Harvesting Sensors: Optimal and Approximated Solutions—0
A Differentiable Physics Engine for Deep Learning in Robotics—0
A Deep Reinforcement Learning Trader without Offline Training—0
An Index Policy Based on Sarsa and Q-learning for Heterogeneous Smart Target Tracking—0
An Independent Study of Reinforcement Learning and Autonomous Driving—0
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