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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 301–325 of 1918 papers

TitleStatusHype
Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence AnalysisCode0
Offline Reinforcement Learning and Sequence Modeling for Downlink Link Adaptation—0
Stochastic Approximation with Unbounded Markovian Noise: A General-Purpose Theorem—0
Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency modelCode0
Optimizing Load Scheduling in Power Grids Using Reinforcement Learning and Markov Decision Processes—0
A Novel Reinforcement Learning Model for Post-Incident Malware Investigations—0
Improve Value Estimation of Q Function and Reshape Reward with Monte Carlo Tree Search—0
DIAR: Diffusion-model-guided Implicit Q-learning with Adaptive Revaluation—0
Multi-Objective-Optimization Multi-AUV Assisted Data Collection Framework for IoUT Based on Offline Reinforcement Learning—0
MFC-EQ: Mean-Field Control with Envelope Q-Learning for Moving Decentralized Agents in Formation—0
Learning Agents With Prioritization and Parameter Noise in Continuous State and Action Space—0
Diffusion-Based Offline RL for Improved Decision-Making in Augmented ARC Task—0
Asymptotic Analysis of Sample-averaged Q-learning—0
Online waveform selection for cognitive radar—0
Hybrid LLM-DDQN based Joint Optimization of V2I Communication and Autonomous Driving—0
VerifierQ: Enhancing LLM Test Time Compute with Q-Learning-based Verifiers—0
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition—0
UNIQ: Offline Inverse Q-learning for Avoiding Undesirable DemonstrationsCode0
Optimized Resource Allocation for Cloud-Native 6G Networks: Zero-Touch ML Models in Microservices-based VNF Deployments—0
Q-WSL: Optimizing Goal-Conditioned RL with Weighted Supervised Learning via Dynamic Programming—0
Learning in complex action spaces without policy gradients—0
Reinforcenment Learning-Aided NOMA Random Access: An AoI-Based Timeliness Perspective—0
Mimicking Human Intuition: Cognitive Belief-Driven Q-Learning—0
Adaptive Knowledge-based Multi-Objective Evolutionary Algorithm for Hybrid Flow Shop Scheduling Problems with Multiple Parallel Batch Processing Stages—0
Optimized Monte Carlo Tree Search for Enhanced Decision Making in the FrozenLake Environment—0
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