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Three essays on sequential learning in search - pursuit games and jury voting problems

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Lee, Viciano (2021) Three essays on sequential learning in search - pursuit games and jury voting problems. PhD thesis, University of Warwick.

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Official URL: http://webcat.warwick.ac.uk/record=b351791

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Abstract

This thesis consists of three papers on different topics on the sequential learning problem. The first paper is a stochastic game model of predator-prey interaction that combines search and pursuit in a single game. In this paper I introduce a novel learning model in which certain parameters of the model could in theory be learned sequentially over time. The second paper in this thesis focuses on the deterministic version of the similar search and pursuit problem. By relaxing the assumption made since Gal and Casas [36], I introduce three sub-problems to the original model and provide general propositions to each of them. The third paper departs from the area of search games and analyzes the optimal voting ordering in sequential juries. Together with Steve Alpern, Bo Chen, and Chenxin Pan, we studied a new version of the Alpern{Chen model [2]. Our paper makes the notion of \ability" more specific by introducing the sealed card model in which the state of Nature (equivalent to innocent or guilty for a legal jury) is the color of a sealed card and the jurors sample other cards in the deck as their `signals' and they vote sequentially. I show that under this model, by voting in Alpern-Chen ordering (median ability, high ability, low ability), the jury ensures the highest average reliability and optimality fraction.

Item Type: Thesis or Dissertation (PhD)
Subjects: Q Science > QA Mathematics
Library of Congress Subject Headings (LCSH): Learning models (Stochastic processes), Game theory, Differential games, Predation (Biology) -- Mathematical models, Voting -- Mathematical models, Probabilities
Official Date: January 2021
Dates:
DateEvent
January 2021UNSPECIFIED
Institution: University of Warwick
Theses Department: Warwick Business School
Thesis Type: PhD
Publication Status: Unpublished
Supervisor(s)/Advisor: Alpern, Steve, 1948- ; Chen, Bo
Format of File: pdf
Extent: viii, 122 leaves : charts
Language: eng

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