Computer Science – Neural and Evolutionary Computing
Scientific paper
2005-02-22
Computer Science
Neural and Evolutionary Computing
27 pages, issued 2005, Java code available at http://purl.org/net/johnnyvon/
Scientific paper
It has been argued that a central objective of nanotechnology is to make products inexpensively, and that self-replication is an effective approach to very low-cost manufacturing. The research presented here is intended to be a step towards this vision. In previous work (JohnnyVon 1.0), we simulated machines that bonded together to form self-replicating strands. There were two types of machines (called types 0 and 1), which enabled strands to encode arbitrary bit strings. However, the information encoded in the strands had no functional role in the simulation. The information was replicated without being interpreted, which was a significant limitation for potential manufacturing applications. In the current work (JohnnyVon 2.0), the information in a strand is interpreted as instructions for assembling a polygonal mesh. There are now four types of machines and the information encoded in a strand determines how it folds. A strand may be in an unfolded state, in which the bonds are straight (although they flex slightly due to virtual forces acting on the machines), or in a folded state, in which the bond angles depend on the types of machines. By choosing the sequence of machine types in a strand, the user can specify a variety of polygonal shapes. A simulation typically begins with an initial unfolded seed strand in a soup of unbonded machines. The seed strand replicates by bonding with free machines in the soup. The child strands fold into the encoded polygonal shape, and then the polygons drift together and bond to form a mesh. We demonstrate that a variety of polygonal meshes can be manufactured in the simulation, by simply changing the sequence of machine types in the seed.
Ewaschuk Robert
Turney Peter
No associations
LandOfFree
Self-Replicating Strands that Self-Assemble into User-Specified Meshes does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Self-Replicating Strands that Self-Assemble into User-Specified Meshes, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Self-Replicating Strands that Self-Assemble into User-Specified Meshes will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-471931