Genetic algorithms are computational models of evolution that play a central role in many artificial life models. We review the history and current scope of research on genetic algorithms in artificial life, using illustrative examples in which the genetic algorithms is used to study how...

The immune system uses many strategies to generate its enormous repertoire of diverse antibodies, but their relative importance is not understood. As part of a larger project to quantify their relative contributions, we have studied how the survival probability of an individual scales with the...

Genetic Algorithms (GAs) and heuristic search are shown to be structurally similar. The strength of the correspondence and its practical consequences are demonstrated by considering the relationship between fitness functions in GAs and the heuristic functions of AI. By examining the extent to...

A measure of search difficulty, fitness distance correlation (FDC), is introduced and its power as a predictor of genetic algorithm (GA) performance is investigated. The sign and magnitude of this correlation can be used to predict the performance of a GA on many problems where the global maxima...

A binary model of the immune system is used to study the effects of evolution on the genetic encoding for antibody molecules. We report experiments which show that the evolution of immune system genes, simulated by the genetic algorithm, can induce a high degree of genetic organization even...

Cross-reactive memory responses occur when the immune system is primed by one strain of a pathogen and challenged with a related, but different strain. Much of the nature of a cross-reactive response is determined by the quantity and distribution of the memory cells, raised to the primary...

Complex adaptive systems (CAS) consist of many interacting and adapting components. Echo is a computational CAS model in which evolving agents are situated in a resource-limited environment. Different views of the notion of species within Echo are compared to biological experiments on relative...

We describe a method of implementing efficient computer simulations of immune systems that have a large number of unique B and/or T cell clones. The method uses an implementation technique called lazy evaluation to create the illusion that all clones are being simulated, while only actually...

This report is concerned with an implementation of a family of models of complex adaptive systems called Echo models. In what follows, you will find: An Introduction to Echo; Information on how to obtain, install and run the Echo system; A description of Echo's graphical interface and...

The problem of protecting computer systems can be viewed generally as the problem of learning to distinguish {\it self} from {\it other}. We describe a method for change detection which is based on the gereration of T cells in the immune system. Mathematical analysis reveals computational costs...