Self-adaptation and Dynamic Environment Experiments with Evolvable Virtual Machines

Abstract

The Department of Information Science is one of six departments that make up the School of Business at the University of Otago. The department offers courses of study leading to a major in Information Science within the BCom, BA and BSc degrees. In addition to undergraduate teaching, the department is also strongly involved in postgraduate research programmes leading to MCom, MA, MSc and PhD degrees. Research projects in spatial information processing, connectionist-based information systems, software engineering and software development, information engineering and database, software metrics, distributed information systems, multimedia information systems and information systems security are particularly well supported.The views expressed in this paper are not necessarily those of the department as a whole. The accuracy of the information presented in this paper is the sole responsibility of the authors. CopyrightCopyright remains with the authors. Permission to copy for research or teaching purposes is granted on the condition that the authors and the Series are given due acknowledgment. Reproduction in any form for purposes other than research or teaching is forbidden unless prior written permission has been obtained from the authors. CorrespondenceThis paper represents work to date and may not necessarily form the basis for the authors' final conclusions relating to this topic. It is likely, however, that the paper will appear in some form in a journal or in conference proceedings in the near future. The authors would be pleased to receive correspondence in connection with any of the issues raised in this paper, or for subsequent publication details. Please write directly to the authors at the address provided below. (Details of final journal/conference publication venues for these papers are also provided on the Department's publications web pages: http://www.otago.ac.nz/informationscience/pubs/). Any other correspondence concerning the Series should be sent to the DPS Coordinator. Abstract. Increasing complexity of software applications forces researchers to look for automated ways of programming and adapting these systems. Self-adapting, self-organising software system is one of the possible ways to tackle and manage higher complexity. A set of small independent problem solvers, working together in a dynamic environment, solving multiple tasks, and dynamically adapting to changing requirements is one way of achieving true self-adaptation in software systems. Our work presents a dynamic multi-task environment and experiments with a self-adapting software system. The Evolvable Virtual Machine (EVM) architecture is a model for building complex hierarchically organised software systems. The intrinsic properties of EVM allow the independent programs to evolve into higher levels of complexity, in a way analogous to multi-level, or hierarchical evolutionary processes. The EVM is designed to evolve structures of self-maintaining, self-adapting ensembles, that are open-ended and hierarchically organised. This arti...

The Concept of Autonomy in Distributed Computation and Multi-Agent Systems

“…A more detailed description of the abstract EVM architecture is given in [Nowostawski et al, 2004]. The experimental results are described in details in [Nowostawski et al, 2005a].…”

“…We present results related to a contemporary model of computation for massively parallel open-ended evolutionary computations based on EVM [Nowostawski et al, 2004]. The model has been used to investigate properties of asynchronously communicating agents in a massively parallel multi-agent system [Nowostawski et al, 2005b]. In this context, we discuss the concept of computational complexity, evolutionary learning and adaptability [Nowostawski et al, 2005a].…”

“…The model has been used to investigate properties of asynchronously communicating agents in a massively parallel multi-agent system [Nowostawski et al, 2005b]. In this context, we discuss the concept of computational complexity, evolutionary learning and adaptability [Nowostawski et al, 2005a]. We will show that with our computational evolutionary system a constant flux of external information is necessary to provide an open-ended increase of complexity of generated (discovered) computational programs.…”

“…Our original desire was to integrate the recent advances from various fields onto a single coherent theoretical model, together with an experimental computational framework which could be used for practical investigations on massively parallel computational framework. Originally designed as an artificial evolution modelling tool [Nowostawski et al, 2005b], the EVM architecture is a model for autonomously interacting, evolving, complex and hierarchically organised software system. The EVM architecture stems from recent advances in evolutionary biology and utilises notions such as specialisation, symbiogenesis [Margulis, 1981], and exaptation [Gould and Vrba, 1982].…”

The Concept of Autonomy in Distributed Computation and Multi-agent Systems

“…These restrictions come directly from an inherent property of the dynamics of the MAS as a distributed asynchronous computational system. We discuss the concept of computational complexity, evolutionary learning and adaptability [12]. Our results suggest that any closed (or fully autonomous) collection of computational agents would be limited in their ability to learn and adapt to new circumstances.…”