Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
The engineering of emergence in complex adaptive systems
Thesis (PhD (Computer Science))--University of Pretoria, 2005.
Saved in:
| Other Authors: | |
|---|---|
| Format: | Thesis |
| Published: |
University of Pretoria
2013
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613472720683008 |
|---|---|
| access_status_str | Open Access |
| author2 | Bishop, Judith |
| author_browse | Bishop, Judith |
| author_facet | Bishop, Judith |
| collection | Thesis |
| dc_rights_str_mv | © 2004, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Thesis (PhD (Computer Science))--University of Pretoria, 2005. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/28103 |
| institution | University of Pretoria (South Africa) |
| last_indexed | 2026-06-10T12:36:41.872Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/28103 The engineering of emergence in complex adaptive systems Bishop, Judith upetd@up.ac.za Potgieter, Anna Elizabeth Gezina Agent-oriented software engineering Heterarchies Agencies Multi-agent systems Agents Bayesian networks Complex adaptive systems Emergence Hyperstructures UCTD Thesis (PhD (Computer Science))--University of Pretoria, 2005. Agent-oriented software engineering is a new software engineering paradigm that is ideally suited to the analysis and design of complex systems. Open distributed environments place a growing demand on complex systems to be adaptive as well. Complex systems that can learn from and adapt to dynamically changing environments are called complex adaptive systems. These systems are characterized by emergent behaviour caused by interactions between system components and the environment. Agent-oriented software engineering methodologies attempt to control emergence during analysis and design by engineering the complex system in such a way that the correct emergent behaviour results during run-time. In a complex adaptive system however, emergent behaviour cannot be predicted during analysis and design, as it evolves only after implementation. By restricting emergent behaviour, as is done in most agent-oriented software engineering approaches, a complex system cannot be fully adaptive as well. We propose the BaBe methodology that will enable a complex system to be adaptive by learning from its environment and modifying its behaviour during run-time. This methodology adds a run-time emergence model consisting of distributed Bayesian behaviour networks to the agent-oriented software engineering lifecycle. These networks are initialised by the human software engineer during analysis and design and deployed by Bayesian agencies (also complex adaptive systems). The Bayesian agents are simple, and collectively they implement distributed Bayesian behaviour networks. These networks, being specialized Bayesian networks, enable the Bayesian agents to collectively mine relationships between emergent behaviours and the interactions that caused them to emerge, in order to adapt the behaviour of the system. The agents are organized into heterarchies of agencies, where each agency activates one or more component behaviour depending on the inference in the underlying Bayesian behaviour network. These agencies assist the human software engineer to bridge the gap between the implementation and the understanding of emergent behaviour in complex adaptive systems. Due to the simplicity of the agents and the minimal communication amongst them, they can be implemented using a commercially available component architecture. We describe a prototype implementation of the Bayesian agencies using Sun’s Enterprise JavaBeans™ component architecture. Computer Science unrestricted 2013-09-07T12:52:19Z 2004-09-22 2013-09-07T12:52:19Z 2004-08-03 2005-09-22 2004-09-22 Thesis Potgieter, A 2004, The engineering of emergence in complex adaptive systems, PhD thesis, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/28103 > http://hdl.handle.net/2263/28103 http://upetd.up.ac.za/thesis/available/etd-09222004-091805/ © 2004, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf application/pdf application/pdf application/pdf University of Pretoria |
| spellingShingle | Agent-oriented software engineering Heterarchies Agencies Multi-agent systems Agents Bayesian networks Complex adaptive systems Emergence Hyperstructures UCTD The engineering of emergence in complex adaptive systems |
| title | The engineering of emergence in complex adaptive systems |
| title_full | The engineering of emergence in complex adaptive systems |
| title_fullStr | The engineering of emergence in complex adaptive systems |
| title_full_unstemmed | The engineering of emergence in complex adaptive systems |
| title_short | The engineering of emergence in complex adaptive systems |
| title_sort | engineering of emergence in complex adaptive systems |
| topic | Agent-oriented software engineering Heterarchies Agencies Multi-agent systems Agents Bayesian networks Complex adaptive systems Emergence Hyperstructures UCTD |
| url | http://hdl.handle.net/2263/28103 http://upetd.up.ac.za/thesis/available/etd-09222004-091805/ |