Work

Adaptive Dynamic Networks as Models for the Immune System and Autocatalytic Sets

Year: 1987

Type: article

Abstract: A general class of network models is described that can be used to present complex adaptive systems. These models have two purposes: On a practical level they are closely based on real biological phenomena, and are intended to model detailed aspects of them. On a more general level, however, they provide a framework to address broader questions concerning evolution, pattern recognition, and other properties of living systems. This paper concentrates on the more general level, illustrating the basic concepts with two examples, a model of the immune system and a model for the spontaneous emergence of autocatalytic sets in a chemically reactive polymer soup. 10 refs., 3 figs.

Source: Annals of the New York Academy of Sciences

DOI: 10.1111/j.1749-6632.1987.tb48728.x

Authors: J. DOYNE FARMER, STUART A. KAUFFMAN, NORMAN H. PACKARD, ALAN S. PERELSON

Institutions: Los Alamos National Laboratory, University of Pennsylvania, University of Illinois Urbana-Champaign

Language: English

Topic: Artificial Immune Systems Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1969306139

FWCI: 0.63

Cites: 8

Cited by: 59

Related to: 10