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dc.contributor.authorSfikas, Konstantinos-
dc.contributor.authorLiapis, Antonios-
dc.contributor.authorYannakakis, Georgios N.-
dc.date.accessioned2024-04-30T10:13:23Z-
dc.date.available2024-04-30T10:13:23Z-
dc.date.issued2023-
dc.identifier.citationSfikas, K., Liapis, A., & Yannakakis, G. N. (2023, July). Controllable exploration of a design space via interactive quality diversity. Genetic and Evolutionary Computation Conference Companion. Lisbon, Portugal. 167-170.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/121628-
dc.description.abstractThis paper introduces a user-driven evolutionary algorithm based on Quality Diversity (QD) search. During a design session, the user iteratively selects among presented alternatives and their selections affect the upcoming results. We implement a variation of the MAP-Elites algorithm where the presented alternatives are sampled from a small region (window) of the behavioral space. After a user selection, the window is centered on the selected individual’s behavior characterization, evolution selects parents from within this window to produce offspring, and new alternatives are sampled. Essentially we define an adaptive system of local QD search, where the user’s selections guide the search towards specific regions of the behavioral space. The system is tested on the generation of architectural layouts, a constrained optimization task, leveraging QD search through a two-archive approach.en_GB
dc.language.isoenen_GB
dc.publisherAssociation for Computing Machineryen_GB
dc.rightsinfo:eu-repo/semantics/openAccessen_GB
dc.subjectEvolutionary computationen_GB
dc.subjectComputer games -- Designen_GB
dc.subjectAlgorithmsen_GB
dc.subjectApplication softwareen_GB
dc.subjectArtificial intelligenceen_GB
dc.subjectComputer communication systemsen_GB
dc.subjectPattern recognitionen_GB
dc.titleControllable exploration of a design space via interactive quality diversityen_GB
dc.typeconferenceObjecten_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.bibliographicCitation.conferencenameGenetic and Evolutionary Computation Conference Companionen_GB
dc.bibliographicCitation.conferenceplaceLisbon, Portugal. 12-14/04/2023en_GB
dc.description.reviewedpeer-revieweden_GB
dc.identifier.doi10.1145/3583133.3590616-
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