The objective of this project is to provide teams of cooperative robots with the appropriate knowledge of their organizational structure and capabilities, along with efficient reasoning mechanisms, to allow them to reorganize “on-the-fly” to achieve their overall team goals more efficiently and effectively in the face of a changing environment and team capabilities. The goal is to establish organizational reasoning as a key component in a new approach to building highly robust cooperative robotic teams. To realize this goal, the new organizational knowledge and reasoning techniques must be incorporated into practical methods and tools for designing and developing real world cooperative robotic systems. The technological objectives of this research will be to
- Develop a team organizational model that describes how organizational concepts such as goals, roles, and individual team members are related
- Develop strategies, techniques, and algorithms for discovering when reorganization is required as well as efficient techniques for reorganizing to allow teams to reach their goals
- Codify these methods and techniques in an automated toolset to ensure that the organizational knowledge is captured and transformed into a form compatible with efficient reasoning techniques
The theories, techniques, methods, and tools developed in research will be used to enhance both undergraduate as well as graduate curriculum in multiagent and cooperative robotic systems. Also, a series of activities designed to impact persons not specifically part of the project are planned with a strong emphasis on pre-college students from elementary to high school. We plan to participate in several summer workshops to motivate pre-college students to select science and technology majors and to reach specific underrepresented groups.
- Scott A. DeLoach. Organizational Model for Adaptive Complex Systems. in Virginia Dignum (ed.) Multi-Agent Systems: Semantics and Dynamics of Organizational Models. IGI Global: Hershey, PA. ISBN: 1-60566-256-9 (March 2009). This chapter copyright 2008, IGI Global, www.igi-pub.com. Posted by permission of the publisher.
- Eric Matson, Scott A. DeLoach, Raj Bhatnagar. Evaluation of Properties in the Transition of Capability Based Agent Organization. Web Intelligence and Agent Systems: An International Journal. (in press).
- Walamitien Oyenan, Scott DeLoach, & Gurdip Singh. A Service-Oriented Approach for Integrating Multiagent System Designs. Proceedings of the Proceedings of 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), Decker, Sichman, Sierra, and Castelfranchi (eds.), May, 10–15, 2009, Budapest, Hungary.
- Scott A. DeLoach, Walamitien Oyenan & Eric T. Matson. A Capabilities Based Model for Artificial Organizations. Journal of Autonomous Agents and Multiagent Systems. Volume 16, no. 1, February 2008, pp. 13-56. DOI: 10.1007/s10458-007-9019-4.
- Scott A. DeLoach, Walamitien Oyenan & Eric T. Matson. A Capabilities Based Theory of Artificial Organizations. accepted for publication in the Journal of Autonomous Agents and Multiagent Systems (2007).
- Scott A. DeLoach and Jorge L. Valenzuela. An Agent-Environment Interaction Model. in L. Padgham and F. Zambonelli (Eds.): AOSE 2006, LNCS 4405, pp. 1-18, 2007. Springer-Verlag, Berlin Heidelberg 2007.
- Eric Matson & Scott A. DeLoach. Enabling Intra-Robotic Capabilities Adaptation Using an Organization-Based Multiagent System. Proceedings of the 2004 IEEE International Conference on Robotics and Automation (ICRA 2004). April 26 – May 1, 2004. New Orleans, LA.
- Eric Matson and Scott DeLoach. Using Dynamic Capability Evaluation to Organize a Team of Cooperative, Autonomous Robots. Proceedings of The 2003 International Conference on Artificial Intelligence (IC-AI'03) June 23-26, 2003, Las Vegas, Nevada, USA.
- Eric Matson, Scott A. DeLoach. Organizational Model for Cooperative and Sustaining Robotic Ecologies. Proceedings of Robosphere 2002, a workshop on Self Sustaining Robotic Ecologies, pp. 5-9. NASA Ames Research Center November 14-15, 2002.
This research is sponsored by the National Science Foundation.
Period of Performance: April 2004 - March 2010