SOTAVerified|Agents Browse Leaderboard About

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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 391–400 of 1918 papers

Title	Date	Tasks	Status	Hype	Score
Deep Q-learning: a robust control approach	Jan 21, 2022	OpenAI GymQ-Learning	CodeCode Available	0	5
Deep Ordinal Reinforcement Learning	May 6, 2019	Deep Reinforcement LearningOpenAI Gym	CodeCode Available	0	5
Orchestrated Value Mapping for Reinforcement Learning	Mar 14, 2022	Ensemble LearningQ-Learning	CodeCode Available	0	5
Deep Q-Learning based Reinforcement Learning Approach for Network Intrusion Detection	Nov 27, 2021	Intrusion DetectionNetwork Intrusion Detection	CodeCode Available	0	5
Automaton-Guided Curriculum Generation for Reinforcement Learning Agents	Apr 11, 2023	Decision MakingQ-Learning	CodeCode Available	0	5
Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation	Jul 24, 2023	GPUQ-Learning	CodeCode Available	0	5
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning	Jul 16, 2020	Policy Gradient MethodsQ-Learning	CodeCode Available	0	5
Performing Deep Recurrent Double Q-Learning for Atari Games	Aug 16, 2019	Atari GamesDeep Reinforcement Learning	CodeCode Available	0	5
ADDQ: Adaptive Distributional Double Q-Learning	Jun 24, 2025	Distributional Reinforcement LearningMuJoCo	CodeCode Available	0	5
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning	Dec 18, 2017	Deep Reinforcement LearningEvolutionary Algorithms	CodeCode Available	0	5

Show:10 25 50

← PrevPage 40 of 192Next →

No leaderboard results yet.