Multi agent collaboration using distributed value functions

Enrique Ferreira and Pradeep Khosla
Proceedings of the IEEE Intelligent Vehicles Symposium (IV 2000), October, 2000, pp. 404 - 409.


Download
  • Adobe portable document format (pdf) (509KB)
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract
In this paper we present the use of distributed value function techniques to reach collaboration in a multiagent system. We apply this method in two different simulation environments: a mobile robot planning/searching task and an intelligent traffic system in an urban environment. In the case of the intelligent traffic system, results show an improvement with respect to a standard fix-time controller and local adaptive controllers. Trajectories for optimal search in an obstacle environment are obtained in the mobile robot case. Some variations to the actual algorithm are pointed out to suit our cases. We conclude discussing our future work.

Notes

Text Reference
Enrique Ferreira and Pradeep Khosla, "Multi agent collaboration using distributed value functions," Proceedings of the IEEE Intelligent Vehicles Symposium (IV 2000), October, 2000, pp. 404 - 409.

BibTeX Reference
@inproceedings{Ferreira_2000_3583,
   author = "Enrique Ferreira and Pradeep Khosla",
   title = "Multi agent collaboration using distributed value functions",
   booktitle = "Proceedings of the IEEE Intelligent Vehicles Symposium (IV 2000)",
   pages = "404 - 409",
   month = "October",
   year = "2000",
}