Amanote Research
Register
Sign In
GA-Based Q-Learning to Develop Compact Control Table for Multiple Agents
doi 10.5772/8054
Full Text
Open PDF
Abstract
Available in
full text
Date
February 1, 2010
Authors
Tadahiko Murata
Yusuke Aoki
Publisher
InTech
Related search
EAQR: A Multiagent Q-Learning Algorithm for Coordination of Multiple Agents
Complexity
Multidisciplinary
Computer Science
Energy-Aware Power Control for a Multiple-Relay Cooperative Network Using Q-Learning
Ramp Metering Control Based on the Q-Learning Algorithm
Cybernetics and Information Technologies
Computer Science
Learning Control and Model-Based Adaptive Control for Coordination of Multiple Manipulators
Transactions of the Society of Instrument and Control Engineers
Development of a Neural Network Based Q Learning Algorithm for Traffic Signal Control
Advanced Engineering Forum
Iterative Learning-Based Formation Control for Multiple Quadrotor Unmanned Aerial Vehicles
International Journal of Advanced Robotic Systems
Six Essential Steps to Develop a Simulation Based Learning Program
Acta Ophthalmologica
Medicine
Ophthalmology
Use of Omic Technologies to Develop Strategies to Control Escherichia Coli From Farm to Table
Learning to Play Pac-Xon With Q-Learning and Two Double Q-Learning Variants
