EAGER: Self-Assembly of Complex Systems

University Of Arkansas, Fayetteville AR

Investigators

Abstract

Abstract for EAGER: Self-Assembly of Complex Systems Intellectual Merit: Self-assembly is a model for how individual components arrange themselves through local interactions to form organized structures. It originated as a model for construction of nanotechnology. The theory of complex systems describes many phenomena in nature, from human intelligence and evolving communities of organisms to human social networks, economies, and cultures. In these systems, complexity emerges in ways that is not immediately obvious from an understanding of the component parts and the relationships between them. In this project, self-assembly will be investigated as a mechanism for creation of complex systems. Self-assembly can be shown to be equivalent to other models of complex systems. In addition, it can be programmed like a computer. A goal of this project is to develop efficient ways to program self-assembly to produce interesting complex systems, which have practical applications. As a beginning to this, we have developed a mapping of self-assembly onto graphs that enables us to use an efficient algorithm to determine the system that is constructed. Thus, self-assembly should be able to generate complex systems and to provide efficient and realistic simulation of those types of systems. In the project, the self-assembly algorithms will be applied to automatic content generation for games, in which the self-assembly automatically creates situations and non-player characters with which players of the game interact. The conjecture is that this will provide more dynamic and realistic game environments, and moreover, will be an interesting test-bed for investigation of the relationship between self-assembly and complex systems. Broader Impacts: This research integrates ideas from chemistry, physics, biology, and computer science to relate self-assembly to complex systems, and to produce potentially transformative tools that will not only improve understanding of complex systems, but also form the basis for innovative complex systems in a variety of application domains. These include nanotechnology, artificial intelligence, art, literature, and computer games. There are many natural phenomena (i.e. human intelligence, living systems) for which traditional symbolic models of computation are only able to capture a part of their essential capabilities and characteristics. Human language is an example. This research conceivably could result in software that is able to produce target systems that capture some of the capability, adaptability, and complexity that is observed in nature. If successful, the project could result in a new paradigm for realistic and complex behavior through computer programs, and would potentially impact not only nanotechnology, but also applications that require automatic generation of realistic content. Moreover, our models of self-assembly can generate this content in tractable ways. In addition, under the direction of the investigator, graduate and undergraduate students will work together in a team on this project, and will be educated in the unique multidisciplinary approach that has been proposed.