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dc.contributor.authorCowan, Tyler James
dc.date.accessioned2021-11-25T16:47:03Z
dc.date.available2021-11-25T16:47:03Z
dc.identifier.urihttp://hdl.handle.net/10464/15464
dc.description.abstractEvolutionary algorithms have a tendency to overuse and exploit particular behaviours in their search for optimality, even across separate runs. The resulting set of monotonous solutions caused by this tendency is a problem in many applications. This research explores different strategies designed to encourage an interesting set of diverse behaviours while still maintaining an appreciable level of efficacy. Embodied agents are situated within an open plane and play against each other in various pursuit game scenarios. The pursuit games consist of a single predator agent and twenty prey agents, with the goal always requiring the predator to catch as many prey as possible before the time limit is reached. The predator's controller is evolved through genetic programming while the preys' controllers are hand-crafted. The fitness of a solution is first calculated in a traditional manner. Inspired by Lehman and Stanley's novelty search strategy, the fitness is then combined with the diversity of the solution to produce the final fitness score. The original fitness score is determined by the number of captured prey, and the diversity score is determined through the combination of four behaviour measurements. Among many promising results, a particular diversity-based evaluation strategy and weighting combination was found to provide solutions that exhibit an excellent balance between diversity and efficacy. The results were analyzed quantitatively and qualitatively, showing the emergence of diverse and effective behaviours.en_US
dc.language.isoengen_US
dc.publisherBrock Universityen_US
dc.subjectdiverseen_US
dc.subjecteffectiveen_US
dc.subjectbehavioursen_US
dc.subjectnoveltyen_US
dc.subjectagentsen_US
dc.titleStrategies for Evolving Diverse and Effective Behaviours in Pursuit Domainsen_US
dc.typeElectronic Thesis or Dissertationen
dc.degree.nameM.Sc. Computer Scienceen_US
dc.degree.levelMastersen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.degree.disciplineFaculty of Mathematics and Scienceen_US
refterms.dateFOA2021-11-25T16:47:03Z


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