The central ideas of the book surround genetics and evolution in an artificial life framework. Topics covered include maintenance of genetic diversity, hierarchical structures and stability of ecosystems. Underpinning these topics are key theoretical developments surrounding network complexity, the development of pattern languages for complex networks and a deeper understanding of the edge of chaos where complex systems live. Practical applications include optimization, gene regulatory networks, modeling the spread of disease and the evolution of ageing.

The reader will gain an insight into the mathematical techniques at the core of artificial life and encounter a sufficient diversity of applications to stimulate new directions in their own field.

Contents:

• Recreating Large-Scale Evolutionary Phenomena (P-M Agapow)
• Approaching Perfect Mixing in a Simple Model of the Spread of an Infectious Disease (D Chu & J Rowe)
• The Formation of Hierarchical Structures in a Pseudo-Spatial Co-Evolutionary Artificial Life Environment (D Cornforth et al.)
• Perturbation Analysis: A Complex Systems Pattern (N Geard et al.)
• A Simple Genetic Algorithm for Studies of Mendelian Populations (C Gondro & J C M Magalhaes)
• Gauging ALife: Emerging Complex Systems (K Kitto)
• Issues in the Scalability of Gate-Level Morphogenetic Evolvable Hardware (J Lee & J Sitte)
• Phenotype Diversity Objectives for Graph Grammar Evolution (M H Luerssen)
• Local Structure and Stability of Model and Real World Ecosystems (D Newth & D Cornforth)
• Quantification of Emergent Behaviors Induced by Feedback Resonance of Chaos (A Pitti et al.)
• Maintaining Explicit Diversity Within Individual Ant Colonies (M Randall)
• Complexity of Networks (R K Standish)
• The Evolution of Aging (O G Woodberry et al.)
• and other papers