Self-organized Complexity in Computer Program Ecosystem

This paper describes self-organized complexity of an ecosystem consisting of computer programs that exhibit life-like behavior. As an artificial life approach to simulating the life-like behavior on a computer, attention should be given to the emergent dynamics by which a new action is brought forth. In considering how to implement such a notion onto a computer, it could be interpreted as the generation of a new algorithm, or the generation of a new code establishing a mapping between a symbol and an information. This paper discusses complex behaviors in our artificial-life system named PROTEAN, that is an ecological model consisting of Turing machines as a platform on which to simulate the emergent dynamics of computer programs. Although the system is not provided with any particular mechanism for self-reproduction, the system is self-organized so that the system constituents can utilize their environments for survival. For the approaches emphasizing simulations on a computer, it is important to understand an emergent process from the viewpoint of computational complexity. Using this ecosystem model, this paper demonstrates how computer programs may be able to achieve life-like behavior, and discusses the relation with their self-organized complexity.