Skip to main content

Adaptive knowledge dynamics and emergent artificial societies: ethnographically based multi-agent simulations of behavioural adaptation in agro-climatic systems

Bharwani, Sukaina (2004) Adaptive knowledge dynamics and emergent artificial societies: ethnographically based multi-agent simulations of behavioural adaptation in agro-climatic systems. Doctor of Philosophy (PhD) thesis, University of Kent. (doi:10.22024/UniKent/01.02.94209) (KAR id:94209)

PDF
Language: English


Download (145MB) Preview
[thumbnail of 846165.pdf]
Preview
This file may not be suitable for users of assistive technology.
Request an accessible format
Official URL:
https://doi.org/10.22024/UniKent/01.02.94209

Abstract

The goal of this research is to enhance an ethnographic understanding of agricultural adaptation to environmental change, within the context of an anthropological theory of 'adaptive dynamics' [Bennett, 1976], using computer-based techniques. An agent-based model was developed to investigate the 'transitional' adaptive strategies of farmers in south-east England based on data collected during fieldwork. Using ethnographic evidence, the model included the interactions of differing structures of knowledge relating to possible environmental change. This resulted in a variety of adaptive, non-adaptive and indeed mal-adaptive responses by agents in the system and thus, differing degrees of success for individual actors and the group as a whole. The choices made in response to change and their consequences were analysed. Success was measured in terms of minimising vulnerability, achieving sustainable adaptation and meeting economic objectives. Adaptive responses classified using criteria proposed by John W. Bennett [1976], under the heading of adaptive dynamics and incorporated within an agent-based model, allowed a refined understanding of the ethnographic data that was collected exposing new insights and areas for further investigation. The agent-based model illustrated the importance of Bennett's model in illuminating the benefits of indigenous strategies for successful adaptation and sustainability. The broad scope of this research means that it is aimed at an interdisciplinary audience. It is organised such that each chapter will contain a general introductory overview which requires little specialist knowledge, while further reading will entail greater technical detail, which will assume some specialist knowledge. Specialist areas covered include simulation toolkits, declarative programming software and social science research methodologies amongst others. This research is intended to be a guide for non-computing anthropologists to understand the potential in developing simple computer models to complement and support their traditional research methods. Experienced modellers may also benefit from specific techniques described from the social sciences domain, such as the participatory knowledge engineering process developed using ethnographic techniques, which may enhance conventional modelling approaches.

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Fischer, Michael D.
Thesis advisor: Ryan, Nick S.
DOI/Identification number: 10.22024/UniKent/01.02.94209
Additional information: This thesis has been digitised by EThOS, the British Library digitisation service, for purposes of preservation and dissemination. It was uploaded to KAR on 25 April 2022 in order to hold its content and record within University of Kent systems. It is available Open Access using a Creative Commons Attribution, Non-commercial, No Derivatives (https://creativecommons.org/licenses/by-nc-nd/4.0/) licence so that the thesis and its author, can benefit from opportunities for increased readership and citation. This was done in line with University of Kent policies (https://www.kent.ac.uk/is/strategy/docs/Kent%20Open%20Access%20policy.pdf). If you feel that your rights are compromised by open access to this thesis, or if you would like more information about its availability, please contact us at ResearchSupport@kent.ac.uk and we will seriously consider your claim under the terms of our Take-Down Policy (https://www.kent.ac.uk/is/regulations/library/kar-take-down-policy.html).
Subjects: G Geography. Anthropology. Recreation > GN Anthropology
Divisions: Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation
SWORD Depositor: SWORD Copy
Depositing User: SWORD Copy
Date Deposited: 29 Sep 2022 13:26 UTC
Last Modified: 29 Sep 2022 13:26 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/94209 (The current URI for this page, for reference purposes)
  • Depositors only (login required):

Downloads

Downloads per month over past year