Translator Disclaimer
20 September 2001 Multirobot learning in an inherently cooperative task
Author Affiliations +
An important need in multi-robot systems is the development of mechanisms that enable robot teams to autonomously generate cooperative behaviors. This paper first briefly presents the Cooperative Multi-robot Observation of Multiple Moving Targets (CMOMMT) application as a rich domain for studying the issues of multi-robot learning of new behaviors. We discuss the results of our hand-generated algorithm for CMOMMT, and then describe our research in generating multi-robot learning techniques for the CMOMMT application, comparing the results to the hand-generated solutions. Our results show that, while the learning approach performs better than random, naive approaches, much room still remains to match the results obtained from the hand-generated approach. The ultimate goal of this research is to develop techniques for multi-robot learning and adaptation that will generalize to cooperative robot applications in many domains, thus facilitating the practical use of multi-robot teams in a wide variety of real-world applications.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lynne E. Parker and Claude Touzet "Multirobot learning in an inherently cooperative task", Proc. SPIE 4364, Unmanned Ground Vehicle Technology III, (20 September 2001);

Back to Top