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Representing intelligent decision making in discrete event simulation : a stochastic neural network approach
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Curram, S. P. (1997) Representing intelligent decision making in discrete event simulation : a stochastic neural network approach. PhD thesis, University of Warwick.
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WRAP_thesis_Curram_1997.pdf - Submitted Version Download (87Mb) | Preview |
Official URL: http://webcat.warwick.ac.uk/record=b1402872~S1
Abstract
The problem of representing decision making behaviour in discrete event simulation was
investigated. Of particular interest was modelling variety in the decisions, where
different people might make different decisions even where the same circumstances hold.
An initial investigation of existing and alternative approaches for representing decision
making was carried out. This led to the suggestion of using a neural network to
represent the decision making behaviour in the form of a multi-criteria probability
distribution based on data of observed decision making.
The feasibility of the stochastic neural network approach was investigated. Models were
fitted using artificial data from discrete and continuous distributions that included the
shape parameters as inputs, and tested against known results from the distributions. Also
a bank simulation was used to collect data from volunteers who controlled the queuing
decisions of customers inside the bank. Models of their behaviour were created and
implemented in the bank simulation to automate the decision making of customers.
The investigation established the feasibility of the approach, although it indicated the
need for substantial amounts of data showing examples of decision making. A hybrid
model that combined the stochastic neural network approach with a rule-based approach
allowed the development of more general models of decision making behaviour.
| Item Type: | Thesis (PhD) |
|---|---|
| Subjects: | H Social Sciences > H Social Sciences (General) R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
| Library of Congress Subject Headings (LCSH): | Decision making , Neural networks (Neurobiology), Stochastic analysis |
| Official Date: | January 1997 |
| Institution: | University of Warwick |
| Theses Department: | Warwick Business School |
| Thesis Type: | PhD |
| Publication Status: | Unpublished |
| Supervisor(s)/Advisor: | Hurrion, R. D. (Robert D.) ; Mingers, John |
| Extent: | xv, 274 leaves |
| Language: | eng |
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