Evolving Asynchronous and Scalable Non-uniform Cellular Automata

Moshe Sipper, Marco Tomassini, Mathieu S. Capcarrère

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We have previously shown that non-uniform cellular automata (CA) can be evolved to perform computational tasks, using the cellular programming algorithm. In this paper we focus on two novel issues, namely, the evolution of asynchronous CAs, and the scalability of evolved synchronous systems. We find that asynchrony presents a more difficult case for evolution though good CAs can still be attained. We describe an empirically derived scaling procedure by which successful CAs of any size may be obtained from a particular evolved system. Our motivation for this study stems in part from our desire to attain realistic systems that axe more amenable to implementation as “evolving ware,” evolware.
Original languageEnglish
Title of host publicationArtificial Neural Nets and Genetic Algorithms
Subtitle of host publicationProceedings of the International Conference in Norwich, U.K., 1997
EditorsGeorge D. Smith, Nigel C. Steele, Rudolf F. Albrecht
Number of pages5
ISBN (Electronic)978-3-7091-6492-1
StatePublished - 1998
Externally publishedYes


  • Cellular Automaton
  • Grid Size
  • Computational Task
  • Logical Step


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