Robustness and Adaptation in Morphogenetic Collective Systems

Project Website

This project was supported by the NSF Robust Intelligence Program (Award #: NSF IIS-1319152).
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

About the Project

The objective of this project was to understand the roles of general morphogenetic principles such as heterogeneity of components, differentiation/re-differentiation of components, and local information exchange among components in the self-organization of biological collectives, and to utilize them to improve the performance of collective artificial systems. The research was conducted on the following four subtasks: (1) Study the effects of morphogenetic principles on self-organizing patterns of heterogeneous collectives using mathematical/computational models. (2) Apply the results of theoretical investigation to construct models of actual self-organizing patterns found in real-world heterogeneous biological collectives. (3) Introduce the morphogenetic principles to existing collective artificial systems and develop mechanisms for programming their structures and behaviors. (4) Measure the overall performance of the proposed morphogenetic collective systems in decentralized optimization and exploration tasks. This research contributes to biology and ecology by providing new theoretical insight into how heterogeneous collectives may self-organize without centralized control, and also to computational science and engineering by bringing an unexplored combination of morphogenetic principles into bio-inspired computational systems. This project has produced societal impacts by providing a novel framework for the design of growing, self-organizing, self-repairing, and evolving artifacts. This project involved the following educational activities: (1) Integration of project outcomes into courses offered through the interdisciplinary graduate certificate program in complex systems science at Binghamton University. (2) Regional high school research program. (3) Public exhibition of morphogenetic collective systems through online videos and simulation software.

Research Team

Principal investigator

Graduate Students



Journal Articles

Conference Proceedings

Conference Presentations

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Online Resources

Contact Us

Please address any inquiries about this project to:

Hiroki Sayama, D.Sc.
Director, Center for Collective Dynamics of Complex Systems
Professor, Department of Systems Science and Industrial Engineering
Binghamton University, State University of New York
P.O. Box 6000, Binghamton, NY 13902-6000

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