Self-assembly Simulation System
This paper describes a software system to model and visualize 3D or 2D selfassembly of groups of autonomous agents. The system makes a physically accurate estimate of the interaction of agents represented as rigid cubic or tetrahedral structures with variable electrostatic charges on the faces and vertices. Local events cause the agents’ charges to change according to user-defined rules or rules generated by genetic algorithms. The system is used as an experimental environment for theoretical and practical study of self-assembly. In particular, the system is used to further develop and test self-assembly properties of meso-blocks.
The paper describes the architecture of the system and a set of experiments which explore passive aggregation and active directed self-assembly of mesoblocks. The experiments demonstrate sensitivity of self-assembly results not only to the logical programming of the agents and initial configuration, but also to physical parameters of the system.
The software system can be applied to the analysis, prediction and design of self-assembly behaviour of agents from atomic- to macro-scales. In particular, it may become a platform for developing design techniques that can be implemented in real nano-scale systems to achieve useful structures.
Unable to display preview. Download preview PDF.
- V. Gerasimov, Y. Guo, G. James, G. Poulton, and P. Valencia (2004) “Multiagent Self-Assembly Simulation Environment,” AAMAS 2004: 1382–1383.Google Scholar
- G. Poulton, Y. Guo, G. James, P. Valencia, V. Gerasimov, and J. Li (2004) “Directed Self-Assembly of 2-Dimensional Mesoblocks using Topdown/Bottom-up Design,” ESOA’ 04 Workshop (during AAMAS-04) New YorkGoogle Scholar
- Y. Guo, G. Poulton, P. Valencia, and G. James (2003) “Designing Self-Assembly for 2-Dimensional Building Blocks,” ESOA’03 Workshop (during AAMAS-03) MelbourneGoogle Scholar
- G. Poulton, Y. Guo, P. Valencia, G. James, M. Prokopenko, and P. Wang (2004) “Designing Enzymes in a Multi-Agent System based on a Genetic Algorithm,” 8th Conference on Intelligent Autonomous Systems, AmsterdamGoogle Scholar
- D. Goldberg (1989) “Genetic algorithms in search, optimisation, and machine learning,” Addison-Wesley Publishing Company, Inc., Reading, MassachusettsGoogle Scholar
- S. Wolfram ed. (1986) “Theory and Application of Cellular Automata,” World Scientific, SingaporeGoogle Scholar
- H. Haken (1983) “Synergetics,” Springer-Verlag, BerlinGoogle Scholar
- H. Garis (1992) “Artificial Embryology: The Genetic Programming of a n Artificial Embryo,” Chapter 14 in book “Dynamic, Genetic, and Chaotic Programming”, ed. B. Soucek and the IRIS Group, WILEYGoogle Scholar
- B. Raguse (2002) “Self-assembly of Hydrogel Mesoblocks,” Personal Communication, CSIROGoogle Scholar
- H. Bojinov, A. Casal, T. Hogg (2000) “Multiagent Control of Selfreconfigurable Robots”, Fourth International Conference on Multi-Agent Systems, Boston, Massachusetts.Google Scholar