{"id":{"repo_id":"duquesne","oai_identifier":"oai:dsc.duq.edu:etd-1585"},"canonical_url":"https://search.dev.ndltd.org/etd/duquesne/oai:dsc.duq.edu:etd-1585","repository":{"repo_id":"duquesne","name":"Duquesne","base_url":"https://dsc.duq.edu/do/oai/"},"display":{"title":"A Genetic Programming Approach to Solving Optimization Problems on Agent-Based Models","abstract":"In this thesis, we present a novel approach to solving optimization problems that are defined on agent-based models (ABM). The approach utilizes concepts in genetic programming (GP) and is demonstrated here using an optimization problem on the Sugarscape ABM, a prototype ABM that includes spatial heterogeneity, accumulation of agent resources, and agents with different attributes. The optimization problem seeks a strategy for taxation of agent resources which maximizes total taxes collected while minimizing impact on the agents over a finite time. We demonstrate how our GP approach yields better taxation policies when compared to simple flat taxes and provide reasons why GP-generated taxes perform well. We also look at ways to improve the performance of the GP optimization method.","abstract_html":"In this thesis, we present a novel approach to solving optimization problems that are defined on agent-based models (ABM). The approach utilizes concepts in genetic programming (GP) and is demonstrated here using an optimization problem on the Sugarscape ABM, a prototype ABM that includes spatial heterogeneity, accumulation of agent resources, and agents with different attributes. The optimization problem seeks a strategy for taxation of agent resources which maximizes total taxes collected while minimizing impact on the agents over a finite time. We demonstrate how our GP approach yields better taxation policies when compared to simple flat taxes and provide reasons why GP-generated taxes perform well. We also look at ways to improve the performance of the GP optimization method.","abstract_has_math":false,"creators":["Garuccio, Anthony"],"institution":null,"degree_name":"MS","degree_level":"Immediate Access","degree_discipline":"Computational Mathematics","degree_department":null,"school":null,"contributors":["Rachael Neilan","Donald Simon","John Kern"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-01-01T08:00:00Z","date_published":"2016-01-01T08:00:00Z","updated_at":"2026-07-24T02:09:46Z","subjects":["Agent Based Modeling","Genetic Programing","Optimal Control","Sugarscape","Taxation"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dsc.duq.edu/etd/569","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Rachael Neilan","Donald Simon","John Kern"]},{"key":"dc:creator","label":"Author","values":["Garuccio, Anthony"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-08-03T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computational Mathematics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Immediate Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Agent Based Modeling","Genetic Programing","Optimal Control","Sugarscape","Taxation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dsc.duq.edu/etd/569"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In this thesis, we present a novel approach to solving optimization problems that are defined on agent-based models (ABM). The approach utilizes concepts in genetic programming (GP) and is demonstrated here using an optimization problem on the Sugarscape ABM, a prototype ABM that includes spatial heterogeneity, accumulation of agent resources, and agents with different attributes. The optimization problem seeks a strategy for taxation of agent resources which maximizes total taxes collected while minimizing impact on the agents over a finite time. We demonstrate how our GP approach yields better taxation policies when compared to simple flat taxes and provide reasons why GP-generated taxes perform well. We also look at ways to improve the performance of the GP optimization method."]},{"key":"dc:title","label":"Title","values":["A Genetic Programming Approach to Solving Optimization Problems on Agent-Based Models"]}]}],"canonical_facts":{"dc:contributor":["Rachael Neilan","Donald Simon","John Kern"],"dc:creator":["Garuccio, Anthony"],"dc:date.available":["2018-08-03T07:00:00Z"],"dc:description.abstract":["In this thesis, we present a novel approach to solving optimization problems that are defined on agent-based models (ABM). The approach utilizes concepts in genetic programming (GP) and is demonstrated here using an optimization problem on the Sugarscape ABM, a prototype ABM that includes spatial heterogeneity, accumulation of agent resources, and agents with different attributes. The optimization problem seeks a strategy for taxation of agent resources which maximizes total taxes collected while minimizing impact on the agents over a finite time. We demonstrate how our GP approach yields better taxation policies when compared to simple flat taxes and provide reasons why GP-generated taxes perform well. We also look at ways to improve the performance of the GP optimization method."],"dc:identifier":["https://dsc.duq.edu/etd/569"],"dc:language":["English"],"dc:subject":["Agent Based Modeling","Genetic Programing","Optimal Control","Sugarscape","Taxation"],"dc:title":["A Genetic Programming Approach to Solving Optimization Problems on Agent-Based Models"],"thesis:degree_discipline":["Computational Mathematics"],"thesis:degree_level":["Immediate Access"],"thesis:degree_name":["MS"]},"updated_at":"2026-07-24T02:09:46Z"}