Studying Artificial Life Using a Simple, General Cellular Model

Some of the major outstanding problems in biology are related to issues of emergence and evolution. These include: (1) how do populations of organisms traverse their adaptive landscapes? (2) what is the relation between adaptedness and tness? (3) the formation of multi-cellular organisms from basic units or cells. In this paper we study these issues using a model which is both general and simple. The system, derived from the CA (cellular automata) model, consists of a two-dimensional grid of interacting organisms which may evolve over time. We rst present designed multi-cellular organisms which display several interesting behaviors including: reproduction, growth, 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 AL models is the opportunities they o er in performing in-depth studies of the evolutionary process. This is accomplished in our case by observing not only phenotypic e ects but also such measures as: tness, operability, energy and the genescape. Our work sheds light on the problems raised above, and o ers a possible path towards the long term two-fold goal of ALife research: (1) increasing our understanding of biology and (2) enhancing our understanding of arti cial models, thereby providing us with the ability to improve their performance.