Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/82048
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dc.contributor.authorDelarosa, Omar-
dc.contributor.authorDong, Hang-
dc.contributor.authorRuan, Mindy-
dc.contributor.authorKhalifa, Ahmed-
dc.date.accessioned2021-10-13T05:23:00Z-
dc.date.available2021-10-13T05:23:00Z-
dc.date.issued2021-
dc.identifier.citationDelarosa, O., Dong, H., Ruan, M., & Khalifa, A. (2021). Mixed-initiative level design with RL brush. EvoMUSART 2021: Artificial Intelligence in Music, Sound, Art and Design. 412-426.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/82048-
dc.description.abstractThis paper introduces RL Brush, a level-editing tool for tile-based games designed for mixed-initiative co-creation. The tool uses reinforcement-learning-based models to augment manual human level-design through the addition of AI-generated suggestions. Here, we apply RL Brush to designing levels for the classic puzzle game Sokoban. We put the tool online and tested it in 39 different sessions. The results show that users using the AI suggestions stay around longer and their created levels on average are more playable and more complex than without.en_GB
dc.language.isoenen_GB
dc.publisherSpringeren_GB
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_GB
dc.subjectComputer games -- Designen_GB
dc.subjectLevel design (Computer science)en_GB
dc.subjectArtificial intelligenceen_GB
dc.subjectMachine learningen_GB
dc.subjectReinforcement learningen_GB
dc.titleMixed-initiative level design with RL brushen_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.conferencenameEvoMUSART 2021: Artificial Intelligence in Music, Sound, Art and Designen_GB
dc.bibliographicCitation.conferenceplaceVirtually, 07-09/04/2021en_GB
dc.description.reviewedpeer-revieweden_GB
dc.identifier.doi10.1007/978-3-030-72914-1_27-
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