Contents

• Abstract
  • Keywords:
• Contents
• Introduction
  • What do we know and what do we believe?
  • Nature is Wonderful
    • The code of life: DNA
    • The working unit: the Cell
    • Division of labour and growth: Multicellularity
  • How did nature get to this Perfection?
  • Should we try to copy nature?
  • What has been done until now
    • Simulating natural processes: Artificial Life
    • Breeding problem solutions: Evolutionary Computation
• The Multicellular Program
  • The Object-Oriented Ontogenetic Programming Paradigm
    • How and why did the idea for the new paradigm evolve?
    • How does it work?
    • Advantages
    • Pitfalls
  • Realization of a Multicellular Program
• How to Breed Multicellular Programs
  • Genetic Programming
    • How does it work?
    • Why not use another technique of program development?
  • The Object-Oriented Ontogenetic Programming System
    • The System
    • Innovations for Genetic Programming
• The Goal: Evolution of Distributed Intelligence
  • Distributed Intelligence - Related Work
    • Amorphous Computing
    • Multiagent Systems
  • Multicellular Programming and Swarm-Programming
  • A Taxonomy for Artificial and Computational Intelligence
• First Experiments
  • Paintable Computing: developing paint that signals and shows defects in a wall as soon as they appear
  • Results
  • Conclusion
• Bibliography
• Index