By Topic

A study on robot task planning problems in multiagent environments

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

2 Author(s)
Kawakami, T. ; Dept. of Inf. & Manage., Hokkaido Women''s Coll., Ebetsu, Japan ; Kakazu, Y.

Attempts to realize an autonomous solving mechanism for a task planning problem by a machine learning system. As a robot task planning problem, the block stacking problem is treated. It is well known as one of the most difficult problems. In particular the difficulties of this problem increase in a multiagent environment where multiple robots exist in a problem domain and they cooperate or negotiate to achieve given tasks effectively. To realize an autonomous planning mechanism, a classifier system is applied to this problem. In this approach, a classifier corresponds to a production rule that instructs the next operation when its conditional part is fully matched for a current state. Each robot has an individual classifier system as the robot task planner

Published in:

Robotics and Automation, 1995. Proceedings., 1995 IEEE International Conference on  (Volume:3 )

Date of Conference:

21-27 May 1995