A mathematical formulation of intelligent agents and their activities

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dc.contributor.advisorRewitzky, Ingriden_ZA
dc.contributor.authorJeftha, Lindseyen_ZA
dc.date.accessioned2014-08-29T12:43:30Z
dc.date.available2014-08-29T12:43:30Z
dc.date.issued2004en_ZA
dc.descriptionIncludes bibliography: leaves 119-126.en_ZA
dc.description.abstractThe task of optimising a collection of objective functions subject to a set of constraints is as important to industry as it is ubiquitous. The importance of this task is evidenced by the amount of research on this subject that is currently in progress. Although this problem has been solved satisfactorily in a number of domains, new techniques and formalisms are still being devised that are applicable in fields as diverse as digital filter design and software engineering. These methods, however, are often computationally intensive, and the heavy reliance on numeric processing usually renders them unintuitive. A further limitation is that many of the techniques treat the problem in top-down fashion. This approach often manifests itself in large, complex systems of equations that are difficult to solve and adapt. By contrast, in a bottom-up approach, a given task is distributed over a collection of smaller components. These components embed behaviour that is determined by simple rules. The interactions between the components, however, often yield behaviour, the complexity of which surpasses what can be captured by the systems of equations that arise from a top-down approach. In this dissertation, we wish to study this bottom-up approach in more detail. Our aim is not to solve the optimisation problem, but rather, to study the smaller components of the approach and their behaviour more closely. To model the components, we choose intelligent agents because these represent a simple yet effective paradigm for capturing complex behaviour with simple rules. We provide several representations for the agents, each of which enables us to model a different aspect of their behaviour. To formulate the representations, we use techniques and concepts from fields such as universal algebra, order theory, domain theory and topology. As part of the formulation we also present a case study to demonstrate how the formulation could be applied.en_ZA
dc.identifier.apacitationJeftha, L. (2004). <i>A mathematical formulation of intelligent agents and their activities</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics. Retrieved from http://hdl.handle.net/11427/6755en_ZA
dc.identifier.chicagocitationJeftha, Lindsey. <i>"A mathematical formulation of intelligent agents and their activities."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 2004. http://hdl.handle.net/11427/6755en_ZA
dc.identifier.citationJeftha, L. 2004. A mathematical formulation of intelligent agents and their activities. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Jeftha, Lindsey AB - The task of optimising a collection of objective functions subject to a set of constraints is as important to industry as it is ubiquitous. The importance of this task is evidenced by the amount of research on this subject that is currently in progress. Although this problem has been solved satisfactorily in a number of domains, new techniques and formalisms are still being devised that are applicable in fields as diverse as digital filter design and software engineering. These methods, however, are often computationally intensive, and the heavy reliance on numeric processing usually renders them unintuitive. A further limitation is that many of the techniques treat the problem in top-down fashion. This approach often manifests itself in large, complex systems of equations that are difficult to solve and adapt. By contrast, in a bottom-up approach, a given task is distributed over a collection of smaller components. These components embed behaviour that is determined by simple rules. The interactions between the components, however, often yield behaviour, the complexity of which surpasses what can be captured by the systems of equations that arise from a top-down approach. In this dissertation, we wish to study this bottom-up approach in more detail. Our aim is not to solve the optimisation problem, but rather, to study the smaller components of the approach and their behaviour more closely. To model the components, we choose intelligent agents because these represent a simple yet effective paradigm for capturing complex behaviour with simple rules. We provide several representations for the agents, each of which enables us to model a different aspect of their behaviour. To formulate the representations, we use techniques and concepts from fields such as universal algebra, order theory, domain theory and topology. As part of the formulation we also present a case study to demonstrate how the formulation could be applied. DA - 2004 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2004 T1 - A mathematical formulation of intelligent agents and their activities TI - A mathematical formulation of intelligent agents and their activities UR - http://hdl.handle.net/11427/6755 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/6755
dc.identifier.vancouvercitationJeftha L. A mathematical formulation of intelligent agents and their activities. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 2004 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/6755en_ZA
dc.language.isoeng
dc.publisher.departmentDepartment of Mathematics and Applied Mathematicsen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherMathematicsen_ZA
dc.titleA mathematical formulation of intelligent agents and their activitiesen_ZA
dc.typeThesis
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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