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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
Music Generation using Human-In-The-Loop Reinforcement Learning—0
Coordinating Ride-Pooling with Public Transit using Reward-Guided Conservative Q-Learning: An Offline Training and Online Fine-Tuning Reinforcement Learning Framework—0
BMG-Q: Localized Bipartite Match Graph Attention Q-Learning for Ride-Pooling Order Dispatch—0
Random-Key Algorithms for Optimizing Integrated Operating Room Scheduling—0
Projection Implicit Q-Learning with Support Constraint for Offline Reinforcement Learning—0
SPEQ: Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning—0
Data-driven inventory management for new products: An adjusted Dyna-Q approach with transfer learning—0
Online inductive learning from answer sets for efficient reinforcement learning exploration—0
An Empirical Study of Deep Reinforcement Learning in Continuing TasksCode0
Cooperative Optimal Output Tracking for Discrete-Time Multiagent Systems: Stabilizing Policy Iteration Frameworks and Analysis—0
Deep Transfer Q-Learning for Offline Non-Stationary Reinforcement Learning—0
β-DQN: Improving Deep Q-Learning By Evolving the Behavior—0
Data-Based Efficient Off-Policy Stabilizing Optimal Control Algorithms for Discrete-Time Linear Systems via Damping Coefficients—0
Dynamic Optimization of Storage Systems Using Reinforcement Learning Techniques—0
Protein Structure Prediction in the 3D HP Model Using Deep Reinforcement Learning—0
A Reinforcement Learning-Based Task Mapping Method to Improve the Reliability of Clustered Manycores—0
HyperQ-Opt: Q-learning for Hyperparameter Optimization—0
ACL-QL: Adaptive Conservative Level in Q-Learning for Offline Reinforcement Learning—0
Multi-Agent Q-Learning for Real-Time Load Balancing User Association and Handover in Mobile Networks—0
Decoding fairness: a reinforcement learning perspectiveCode0
MacLight: Multi-scene Aggregation Convolutional Learning for Traffic Signal ControlCode0
Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework—0
Neural-Network-Driven Reward Prediction as a Heuristic: Advancing Q-Learning for Mobile Robot Path Planning—0
Integrated trucks assignment and scheduling problem with mixed service mode docks: A Q-learning based adaptive large neighborhood search algorithm—0
PickLLM: Context-Aware RL-Assisted Large Language Model Routing—0
Edge Delayed Deep Deterministic Policy Gradient: efficient continuous control for edge scenarios—0
DRL4AOI: A DRL Framework for Semantic-aware AOI Segmentation in Location-Based ServicesCode0
Demonstration Selection for In-Context Learning via Reinforcement Learning—0
Comparative Analysis of Multi-Agent Reinforcement Learning Policies for Crop Planning Decision Support—0
Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning—0
Q-learning-based Model-free Safety Filter—0
Dynamic Retail Pricing via Q-Learning -- A Reinforcement Learning Framework for Enhanced Revenue Management—0
Time-Scale Separation in Q-Learning: Extending TD() for Action-Value Function Decomposition—0
Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise—0
Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning—0
Mitigating Relative Over-Generalization in Multi-Agent Reinforcement Learning—0
Coverage Analysis for Digital Cousin Selection -- Improving Multi-Environment Q-Learning—0
Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization—0
Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learning—0
Enhancing Robot Assistive Behaviour with Reinforcement Learning and Theory of MindCode0
Real-World Offline Reinforcement Learning from Vision Language Model Feedback—0
Reinforcement Learning for Adaptive Resource Scheduling in Complex System Environments—0
Asymptotic regularity of a generalised stochastic Halpern scheme with applications—0
Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning—0
Maximizing User Connectivity in AI-Enabled Multi-UAV Networks: A Distributed Strategy Generalized to Arbitrary User Distributions—0
Think Smart, Act SMARL! Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement LearningCode0
Temporal-Difference Learning Using Distributed Error SignalsCode0
Simulation of Nanorobots with Artificial Intelligence and Reinforcement Learning for Advanced Cancer Cell Detection and TrackingCode0
Regret of exploratory policy improvement and q-learning—0
HAVER: Instance-Dependent Error Bounds for Maximum Mean Estimation and Applications to Q-Learning and Monte Carlo Tree Search—0
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