Studying Artificial Life Using a Simple, General Cellular Model

Research output: Contribution to journalArticlepeer-review


Some of the major outstanding problems in biology are related to issues of emergence and evolution. These include: (a) how populations of organisms traverse their adaptive landscapes; (b) what the relation between adaptedness and fitness is; and (c) the formation of multicellular organisms from basic units or cells. In this article we study these issues using a model that is both general and simple. The system, derived from the CA (cellular automata) model, consists of a two-dimensional grid of interacting organisms that may evolve over time. We first present designed multicellular organisms that display several interesting behaviors, including reproduction, growth, and mobility. We then turn our attention to evolution in various environments, including an environment in which competition for space occurs, an IPD (Iterated Prisoner's Dilemma) environment, an environment of spatial niches, and an environment of temporal niches. One of the advantages of artificial life (AL) models is the opportunities they offer in performing in-depth studies of the evolutionary process. This is accomplished in our case by observing not only phenotypic effects but also such measures as fitness, operability, energy and the genescape. Our work sheds light on the problems raised above, and offers a possible path toward the long-term, two-fold goal of ALife research: (a) increasing our understanding of biology, and (b) enhancing our understanding of artificial models, thereby providing us with the ability to improve their performance.
Original languageEnglish GB
Pages (from-to)1-35
Number of pages35
JournalArtificial Life
Issue number1
StatePublished - 1994
Externally publishedYes


  • artificial life
  • emergence
  • environment
  • evolution
  • iterated prisoner's dilemma
  • multicellularity
  • nonuniform cellular automata
  • self-reproduction


Dive into the research topics of 'Studying Artificial Life Using a Simple, General Cellular Model'. Together they form a unique fingerprint.

Cite this