Evolvable Virtual Machines
The Evolvable Virtual Machine abstract architecture (EVMA) is a computational architecture for dynamic hierarchically organised virtual machines. The concrete EVM instantiation (EVMI) builds on traditional stack-based models of computation and extends them by notions of hierarchy and reflection on the virtual machine level. The EVM Uni- verse is composed of a number of autonomous and asynchronously communicating EVM machines. The main contribution of this work lies in the new model of computation and in the architecture itself: a novel, compact, flexible and expressive representation of distributed concurrent computation. The EVMA provides a way of expressing and modelling auto-catalytic networks composed of a hierarchical hypercycle of autopoietic subsystems characterised by self-adaptable structural tendencies and self-organised criticality. EVMA provides capabilities for: a) self-learning of dynamical patterns through continuous observation of computable environments, b) self-compacting and generalisa- tion of existing program structures, c) emergence of efficient and robust communication code through appropriate machine assembly on both ends of communication channel. EVMA is in one sense a multi-dimensional generalisation of stack machine with the pur- pose of modelling concurrent asynchronous processing. EVMA approach can be also seen as a meta-evolutionary theory of evolution. The EVMA is designed to model systems that mimic living autonomous and adaptable computational processes. The EVMI prototype has been designed and developed to conduct experimental studies on complex evolving systems. The generality of our approach not only provides the means to experiment with complex hierarchical, computational and evolutionary systems, but it provides a useful model to evaluate, share and discuss the complex hierarchical systems in general. The EVMA provides a novel methodology and language to pursue research, to understand and to talk about evolution of complexity in living systems. In this thesis, we present the simple single-cell EVMI framework, discuss the multi-cell EVM Universe architecture, present experimental results, and propose further extensions, experimental studies, and possible hardware implementations of the EVMI.
Advisor: Purvis, Martin; Cranefield, Stephen
Degree Name: Doctor of Philosophy
Degree Discipline: Information Science
Publisher: University of Otago
Keywords: natural evolution; natural life; computation; virtual machine; evolutionary computing; artificial evolution; artificial life; parallel computing; autonomic computing; self-organised systems; autopoiesis; autocatalytic cycles; hypercycles; hierarchies; autonomy
Research Type: Thesis