Cart (Loading....) | Create Account
Close category search window
 

A study on Reinforcement Learning system for agents to acquire cooperative behavior in gap-widening situations

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Kitakoshi, D. ; Dept. of Comput. Sci., Tokyo Nat. Coll. of Technol., Tokyo, Japan ; Miyauchi, R. ; Suzuki, M.

This article proposes an Interactive Hierarchical Reinforcement Learning system (IH-RL). The goal of our study is that the agents using the IH-RL acquire adequate behaviors to cooperative in “gap-widening” situations. Such situations are observed in a variety of real-world environments (e.g., economic gaps between humans or between companies in a community), and are thus important to solve. Computer simulations are carried out to evaluate the basic performance of our system. The results showed that the IH-RL resolves gap-widening situations through agents' cooperative behaviors.

Published in:

Robotic Intelligence In Informationally Structured Space (RiiSS), 2011 IEEE Workshop on

Date of Conference:

11-15 April 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.