Evolving Globally Synchronized Cellular Automata

Rajarshi Das, James P. Crutchfield, Melanie Mitchell and James E. Hanson

Working Papers from Santa Fe Institute

Abstract: How does an evolutionary process interact with a decentralized, distributed system in order to produce globally coordinated behavior? Using a genetic algorithm (GA) to evolve cellular automata (CAs), we show that the evolution of spontaneous synchronization, one type of emergent coordination, takes advantage of the underlying medium's potential to form embedded particles. The particles, typically phase defects between sychronous regions, are designed by the evolutionary process to resolve frustrations in the global phase. We describe in detail one typical solution discovered by the GA, delineating the discovered synchronization algorithm in terms of embedded particles and their interactions. We also use the particle-level description to analyze the evolutionary sequence by which this solution was discovered. Our results have implications both for understanding emergent collective behavior in natural systems and for the automatic programming of decentralized spatially extended multiprocessor systems.

Date: 1995-01
References: Add references at CitEc
Citations: View citations in EconPapers (5)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wop:safiwp:95-01-005

Access Statistics for this paper

More papers in Working Papers from Santa Fe Institute Contact information at EDIRC.
Bibliographic data for series maintained by Thomas Krichel ().