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 1–25 of 1918 papers

Title	Date	Tasks	Status	Hype	Score
ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy	Feb 8, 2025	Q-LearningSafe Exploration	CodeCode Available	3	5
Simplifying Deep Temporal Difference Learning	Jul 5, 2024	Q-LearningReinforcement Learning (RL)	CodeCode Available	3	5
Flow Q-Learning	Feb 4, 2025	Action GenerationD4RL	CodeCode Available	3	5
Streaming Deep Reinforcement Learning Finally Works	Oct 18, 2024	Atari GamesDeep Reinforcement Learning	CodeCode Available	3	5
rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch	Sep 3, 2019	Deep Reinforcement LearningQ-Learning	CodeCode Available	2	5
Digi-Q: Learning Q-Value Functions for Training Device-Control Agents	Feb 13, 2025	Q-LearningReinforcement Learning (RL)	CodeCode Available	2	5
Safe Multi-Agent Reinforcement Learning with Bilevel Optimization in Autonomous Driving	May 28, 2024	Autonomous DrivingBilevel Optimization	CodeCode Available	2	5
Offline RL for Natural Language Generation with Implicit Language Q Learning	Jun 5, 2022	Language ModellingOffline RL	CodeCode Available	2	5
Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather	Jul 2, 2024	Data AugmentationLIDAR Semantic Segmentation	CodeCode Available	2	5
ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency	Nov 29, 2022	Decision MakingMulti-agent Reinforcement Learning	CodeCode Available	2	5
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning	Aug 12, 2022	D4RLOffline RL	CodeCode Available	2	5
Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning	Mar 2, 2024	DecoderMulti-agent Reinforcement Learning	CodeCode Available	2	5
Pretrained LLM Adapted with LoRA as a Decision Transformer for Offline RL in Quantitative Trading	Nov 26, 2024	Offline RLparameter-efficient fine-tuning	CodeCode Available	2	5
Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding	Mar 12, 2024	Multi-Agent Path FindingMulti-agent Reinforcement Learning	CodeCode Available	2	5
Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problem	Dec 8, 2020	Combinatorial OptimizationQ-Learning	CodeCode Available	1	5
Coarse-to-Fine Q-attention: Efficient Learning for Visual Robotic Manipulation via Discretisation	Jun 23, 2021	Continuous ControlQ-Learning	CodeCode Available	1	5
Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?	Dec 1, 2020	Feature EngineeringQ-Learning	CodeCode Available	1	5
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning	Mar 9, 2023	Offline RLQ-Learning	CodeCode Available	1	5
CCLF: A Contrastive-Curiosity-Driven Learning Framework for Sample-Efficient Reinforcement Learning	May 2, 2022	Data AugmentationQ-Learning	CodeCode Available	1	5
Conservative Q-Learning for Offline Reinforcement Learning	Jun 8, 2020	continuous-controlContinuous Control	CodeCode Available	1	5
Benchmarking Batch Deep Reinforcement Learning Algorithms	Oct 3, 2019	BenchmarkingDeep Reinforcement Learning	CodeCode Available	1	5
Reinforcement Learning in High-frequency Market Making	Jul 14, 2024	Q-Learningreinforcement-learning	CodeCode Available	1	5
A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games	Jul 18, 2022	Atari GamesDeep Reinforcement Learning	CodeCode Available	1	5
Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19	Feb 9, 2021	BenchmarkingQ-Learning	CodeCode Available	1	5
Backprop-Free Reinforcement Learning with Active Neural Generative Coding	Jul 10, 2021	Q-Learningreinforcement-learning	CodeCode Available	1	5

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