Grouping complex systems for classification and parallel simulation

Abstract

This thesis is concerned with grouping complex systems by means of concurrent model, in order to aid in (i) formulation of classifications and (ii) induction of parallel simulation programs. It observes, and seeks f~ furmalize _ and then exploit, the strong structural resemblance between complex systems and occam programs. The thesis hypothesizes that groups of complex systems may be discriminated according to shared structural and behavioural characteristics. Such an analysis of the complex systems domain may be performed in the abstract with the aid of a model for capturing interesting features of complex systems. The resulting groups would form a classification of complex systems. An additional hypothesis is that, insofar as the model is able to capture sufficient . programmatic information, these groups may be used to define, automatically, algorithmic skeletons for the concurrent simulation of complex systems. In order to test these hypotheses, a specification model and an accompanying formal notation are developed. The model expresses properties of complex systems in a mixture of object-oriented and process-oriented styles .. The model is then used as the basis for performing both classification and automatic induction of parallel simulation programs. The thesis takes the view that specification models should not be overly complex, especially if the specifications are meant to be executable. Therefore the requirement for explicit consideration of concurrency on the part of specifiers is minimized. The thesis formulates specifications of classes of cellular automata and neural networks according to the proposed model. Procedures for verificati6If - and induction of parallel simulation programs are also included