We have considered several different types of ABM models, relevant to ALife, from the perspective of novelty.
The first type were generic ABMs with closed agents, but capable of exhibiting evolutionary dynamics. However, by the very definition of closed agents, these will have severely limited potential for novel behaviour--at the agent level. In essence, the programmer must pre-specify and code the complete range of possible variations the agents can undergo. In spite of the limited potential for novelty creation, this type of model is often very powerful and can provide and has already provided a number of important insights into various theoretical and practical problems of selection and evolutionary dynamics. However, it is not fruitful with respect to its ability to create novelty.
This limitation can partly be overcome by a modification to the agent-based paradigm. If the agents are open--if they have embedded general purpose computing capability--then there is obviously a greater potential for spontaneous creation of novelty. Examples of existing artificial life systems which follow this principle are Tierra or Avida. However, these models seem ultimately to be disappointing; evolutionary development (of the agents) reaches a plateau and effectively ceases. How the phenomenology of these models can be substantially improved upon is an open research question of fundamental importance to the understanding of ALife modelling.
In real life, the emergence of new types of proteins with new functions is, in an evolutionary perspective, an example of a major source of perpetual novelty. The characteristic feature of real chemistries is that macromolecules and molecular complexes show fundamentally novel behaviours relative to the constituting particles; we say that the macromolecule constitutes a new entity which constrains its parts from the ``top-down''. We propose that similar mechanisms, implemented in ACs, may substantially enhance the creation of novelty in such models.
Copyright © 2002 All Rights Reserved.