Computation in artificially evolved, non-uniform cellular automata

Moshe Sipper, Marco Tomassini

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


Cellular automata are dynamical systems in which space and time are discrete, that operate according to local interaction rules. Designing such systems to exhibit a specific behavior or to perform a particular task is highly complicated, thus severely limiting their applications. We study non-uniform cellular automata, focusing on the evolution of such systems to perform computational tasks, via a parallel evolutionary algorithm, known as cellular programming. We present the algorithm and demonstrate that high-performance systems can be evolved to perform two non-trivial computational tasks, density and random number generation.

Original languageEnglish
Pages (from-to)81-98
Number of pages18
JournalTheoretical Computer Science
Issue number1
StatePublished - 28 Mar 1999
Externally publishedYes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Computation in artificially evolved, non-uniform cellular automata'. Together they form a unique fingerprint.

Cite this