Abstract
Evolutionary simulation modelling is presented as a methodology involving the application of modelling techniques developed within the artificial sciences to evolutionary problems. Although modelling work employing this methodology has a long and interesting history, it has remained, until recently, a relatively underdeveloped practice, lacking a unifying theoretical framework.
Within this thesis, evolutionary simulation modelling will be defined as the use of simulations, constructed under constraints imposed by evolutionary theories, to explore the adequacy of these theories, through the modelling of an adaptive system's ongoing evolution.
Evolutionary simulation models may be considered to lie within the field of artificial life, since its concerns include theories of life, evolution, dynamical systems, and the relationship between artificial and natural adaptive systems. Simultaneously, evolutionary simulation modelling should be regarded as distinct from, yet complementing, existing evolutionary modelling techniques within the biological sciences.
The ambit of evolutionary simulation modelling includes those systems towards which one is able to take the evolutionary perspective, i.e., systems comprising agents which change over time through the action of some adaptive process. This perspective is broad, allowing evolutionary simulation models to address linguistic models of glossogenetic change, anthropological models of
cultural development, and models of economic learning, as well as models of biological evolution.
Once this methodology has been defined, it is applied to a group of problems current within theoretical biology, concerning the evolution of natural signalling systems.
The ubiquity of natural communication is a well attested phenomenon. However, recently the utility of such communication within a world populated by neo-Darwinian selfish individuals has been questioned. Theoretical models proposed to account for the existence of signalling within the animal kingdom are reviewed, and evolutionary simulation models are constructed in an attempt
to assess these theories. Specifically, models of the evolution of complex symmetry, and models of the evolution of honesty, are addressed.
Within this thesis, evolutionary simulation modelling will be defined as the use of simulations, constructed under constraints imposed by evolutionary theories, to explore the adequacy of these theories, through the modelling of an adaptive system's ongoing evolution.
Evolutionary simulation models may be considered to lie within the field of artificial life, since its concerns include theories of life, evolution, dynamical systems, and the relationship between artificial and natural adaptive systems. Simultaneously, evolutionary simulation modelling should be regarded as distinct from, yet complementing, existing evolutionary modelling techniques within the biological sciences.
The ambit of evolutionary simulation modelling includes those systems towards which one is able to take the evolutionary perspective, i.e., systems comprising agents which change over time through the action of some adaptive process. This perspective is broad, allowing evolutionary simulation models to address linguistic models of glossogenetic change, anthropological models of
cultural development, and models of economic learning, as well as models of biological evolution.
Once this methodology has been defined, it is applied to a group of problems current within theoretical biology, concerning the evolution of natural signalling systems.
The ubiquity of natural communication is a well attested phenomenon. However, recently the utility of such communication within a world populated by neo-Darwinian selfish individuals has been questioned. Theoretical models proposed to account for the existence of signalling within the animal kingdom are reviewed, and evolutionary simulation models are constructed in an attempt
to assess these theories. Specifically, models of the evolution of complex symmetry, and models of the evolution of honesty, are addressed.
| Original language | English |
|---|---|
| Publisher | University of Sussex |
| Publication status | Published - 1997 |