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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 331–340 of 1918 papers

Title	Date	Tasks	Status	Hype	Score
An Empirical Study of Deep Reinforcement Learning in Continuing Tasks	Jan 12, 2025	Deep Reinforcement LearningMuJoCo	CodeCode Available	0	5
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks	Apr 8, 2023	Deep Reinforcement LearningGraph Neural Network	CodeCode Available	0	5
Deep Recurrent Q-Learning vs Deep Q-Learning on a simple Partially Observable Markov Decision Process with Minecraft	Mar 11, 2019	MinecraftQ-Learning	CodeCode Available	0	5
Goal Recognition as Reinforcement Learning	Feb 13, 2022	Q-Learningreinforcement-learning	CodeCode Available	0	5
Action Candidate Driven Clipped Double Q-learning for Discrete and Continuous Action Tasks	Mar 22, 2022	Q-Learning	CodeCode Available	0	5
Deep Reinforcement Learning Algorithms for Option Hedging	Apr 7, 2025	Deep Reinforcement LearningQ-Learning	CodeCode Available	0	5
Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge Distillation	Sep 1, 2021	Deep Reinforcement LearningGeneral Reinforcement Learning	CodeCode Available	0	5
Deep Reinforcement Learning for Control of Probabilistic Boolean Networks	Sep 7, 2019	Deep Reinforcement LearningQ-Learning	CodeCode Available	0	5
Deep-Q Learning with Hybrid Quantum Neural Network on Solving Maze Problems	Apr 20, 2023	Q-Learningreinforcement-learning	CodeCode Available	0	5
Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning	Jul 5, 2021	Atari GamesDeep Reinforcement Learning	CodeCode Available	0	5

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