Year of Graduation

2017

Level of Access

Restricted Access Thesis

Embargo Period

5-25-2017

Department or Program

Computer Science

First Advisor

Clare Bates Congdon

Abstract

This paper examines the impact of changes in various economic and environmental variables on changes in global crop yields using techniques from genetics-based machine learning (GBML). Specifically, it presents an implementation of a learning classifier system (LCS)––a powerful evolutionary algorithm for rule-based learning––for the analysis of a large set of agricultural data, as well as the results of that analysis.

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