SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1251–1275 of 1918 papers

TitleStatusHype
GenCos' Behaviors Modeling Based on Q Learning Improved by Dichotomy—0
Cooperative Control of Mobile Robots with Stackelberg Learning—0
QPLEX: Duplex Dueling Multi-Agent Q-LearningCode1
Momentum Q-learning with Finite-Sample Convergence Guarantee—0
Deep Reinforcement Learning for Dynamic Spectrum Sensing and Aggregation in Multi-Channel Wireless Networks—0
Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient—0
A Comparative Study of AI-based Intrusion Detection Techniques in Critical Infrastructures—0
EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL—0
Trade-off on Sim2Real Learning: Real-world Learning Faster than Simulations—0
A Machine Learning Approach for Task and Resource Allocation in Mobile Edge Computing Based Networks—0
Multi-agent Reinforcement Learning in Bayesian Stackelberg Markov Games for Adaptive Moving Target Defense—0
Same-Day Delivery with Fairness—0
Meta-Gradient Reinforcement Learning with an Objective Discovered Online—0
Reinforcement Learning-Enabled Decision-Making Strategies for a Vehicle-Cyber-Physical-System in Connected Environment—0
DRIFT: Deep Reinforcement Learning for Functional Software Testing—0
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient LearningCode0
Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent—0
Qgraph-bounded Q-learning: Stabilizing Model-Free Off-Policy Deep Reinforcement Learning—0
Single-partition adaptive Q-learningCode0
Revisiting Fundamentals of Experience ReplayCode0
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement LearningCode1
The Mean-Squared Error of Double Q-LearningCode0
Neural Interactive Collaborative FilteringCode1
Reward Machines for Cooperative Multi-Agent Reinforcement LearningCode1
Hedging using reinforcement learning: Contextual k-Armed Bandit versus Q-learning—0
Show:102550
← PrevPage 51 of 77Next →

No leaderboard results yet.