Layered Learning In Multiagent Systems: A Winning Approach To Robotic Soccer (Intelligent Robotics And Autonomous Agents),Used

Layered Learning In Multiagent Systems: A Winning Approach To Robotic Soccer (Intelligent Robotics And Autonomous Agents),Used

In Stock
SKU: SONG0262194384
Brand: Bradford Book
$10.73 $15.33
Save $4.60
Quantity
Add to wishlist
Add to compare

Processing time: 1-3 days

US Orders Ships in: 3-5 days

International Orders Ships in: 8-12 days

Return Policy: 15-days return on defective items

Payment Option
Payment Methods

Help

If you have any questions, you are always welcome to contact us. We'll get back to you as soon as possible, withing 24 hours on weekdays.

Customer service

All questions about your order, return and delivery must be sent to our customer service team by e-mail at yourstore@yourdomain.com

Sale & Press

If you are interested in selling our products, need more information about our brand or wish to make a collaboration, please contact us at press@yourdomain.com

This book looks at multiagent systems that consist of teams of autonomous agents acting in realtime, noisy, collaborative, and adversarial environments.This book looks at multiagent systems that consist of teams of autonomous agents acting in realtime, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems. First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to switch roles while acting. Second, it presents layered learning, a generalpurpose machinelearning method for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable with existing machinelearning methods. Third, the book introduces a new multiagent reinforcement learning algorithmteampartitioned, opaquetransition reinforcement learning (TPOTRL)designed for domains in which agents cannot necessarily observe the statechanges caused by other agents' actions. The final contribution is a fully functioning multiagent system that incorporates learning in a realtime, noisy domain with teammates and adversariesa computersimulated robotic soccer team. Peter Stone's work is the basis for the CMUnited Robotic Soccer Team, which has dominated recent RoboCup competitions. RoboCup not only helps roboticists to prove their theories in a realistic situation, but has drawn considerable public and professional attention to the field of intelligent robotics. The CMUnited team won the 1999 Stockholm simulator competition, outscoring its opponents by the rather impressive cumulative score of 1100.

⚠️ WARNING (California Proposition 65):

This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.

For more information, please visit www.P65Warnings.ca.gov.

Recently Viewed