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Title: Three papers on decision theoretic agent-based modelling in demography
Author: Gray, Jonathan
ISNI:       0000 0004 6497 0823
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2017
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This thesis consists of three papers, which address Agent-Based Modelling (AM) as a methodology in demography, focusing on the modelling of decision making processes. The discussion begins by assessing the utility of AM as a methodology and some of the issues peculiar to it, and argues that the modelling of choice is of special significance in the demographic context. Of the three papers, the first one outlines an approach to model development combining aspects of game theory, and decision theory. It then contrasts the effect of four choice models on the behaviour of a simulation based on qualitative accounts of the disclosure behaviours surrounding alcohol misuse in pregnancy. The second paper applies this approach to help-seeking in older adult care, drawing on survey data to parameterise and validate the model. Simulation results, and variance-based sensitivity analysis indicate that a model of decision making which incorporates a representation of the interactions between agents are necessary to reproduce observed rates of caregiving. The third paper reports experiments designed to validate the choice behaviour of agents in the older adult care model. I examine human decision making about paired gambles from experience, where the pair has some features common to both choices. I report results for eight decision problems undertaken by 20 participants, and contrast the predictive ability of four models of decision making. I then estimate parameters to maximise the fit where possible, and find that while the best performance is offered by decision models with a representation of the problem, they do not offer a significant advantage over heuristic methods. I discuss the implications of this, in the context of the original agent-based model, and for agent-based modelling more generally.
Supervisor: Bijak, Jakub ; Bullock, Seth Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available