CACM logo

ACM TechNews

A New Artificial Intelligence Technique to Speed the Planning of Tasks When Resources Are Limited

Universidad Carlos III in Madrid (UC3M) researchers have developed an artificial intelligence technique that can automatically create plans and quickly solve problems in situations with limited resources.

They say the technique can be applied to logistics, autonomous control of robots, fire extinguishing, and online learning. The goal is to get the system to independently find an ordered sequence of actions that will enable objectives to be reached.

"With regard to time, our technique is three to 10 times faster, and with regard to quality, our solutions offer similar quality to that obtained by the best technique that is currently available," says UC3M's Angel Garcia Olaya. "Now we are making modifications that we hope will allow us to give still greater quality to our solutions."

The technique can be applied to any industry in which it makes sense to implement automatic planning. For example, Spain's Ministry of Industry, Tourism and Commerce used the technique to create a system of automatic planning for the multimodal transport of goods.

The researchers also are using the system in conjunction with the European Space Agency for planning and observation operations in space.

From Carlos III University of Madrid (Spain) 
View Full Article

Abstracts Copyright © 2012 Information Inc. External Link, Bethesda, Maryland, USA 

Post a comment...
Name: Anonymous

Signed and anonymous comments submitted to this site are moderated and will appear if they are relevant to the topic and not abusive. Your comment will appear with your username if you are signed into the site, and will be anonymous if you are not signed in. View our policy on comments

Tools For Readers

Bookmark and Share
Default Font Size Large Font Size X-Large Font Size Text Size

Related ACM Resources

Conferences:

Courses:


About Communications | Join ACM External Link | Renew External Link | Subscribe External Link | Sign In | For Authors | For Advertisers External Link | Privacy | Site Map | Help | Contact Us | Mobile Site

Copyright © 2012 by the ACM. All rights reserved.