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DC Field | Value | Language |
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dc.contributor.author | Cerny Green, Michael | - |
dc.contributor.author | Mugrai, Luvneesh | - |
dc.contributor.author | Khalifa, Ahmed | - |
dc.contributor.author | Togelius, Julian | - |
dc.date.accessioned | 2021-10-12T10:32:36Z | - |
dc.date.available | 2021-10-12T10:32:36Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Cerny Green, M., Mugrai, L., Khalifa, A., & Togelius, J. (2020). Mario level generation from mechanics using scene stitching. 2020 IEEE Conference on Games (CoG), Osaka. 49-56. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/82027 | - |
dc.description.abstract | Video game tutorials allow players to gain mastery over game skills and mechanics. To hone players' skills, it is beneficial from practicing in environments that promote individual player skill sets. However, automatically generating environments which are mechanically similar to one-another is a non-trivial problem. This paper presents a level generation method for Super Mario by stitching together pre-generated "scenes" that contain specific mechanics, using mechanic-sequences from agent playthroughs as input specifications. Given a sequence of mechanics, the proposed system uses an FI-2Pop algorithm and a corpus of scenes to perform automated level authoring. The proposed system outputs levels that can be beaten using a similar mechanical sequence to the target mechanic sequence but with a different playthrough experience. We compare the proposed system to a greedy method that selects scenes that maximize the number of matched mechanics. Unlike the greedy approach, the proposed system is able to maximize the number of matched mechanics while reducing emergent mechanics using the stitching process. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Computer games -- Design | en_GB |
dc.subject | Artificial intelligence | en_GB |
dc.title | Mario level generation from mechanics using scene stitching | en_GB |
dc.type | conferenceObject | en_GB |
dc.rights.holder | The 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.conferencename | 2020 IEEE Conference on Games (CoG) | en_GB |
dc.bibliographicCitation.conferenceplace | Osaka, Japan, 24-27/08/2020 | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.identifier.doi | 10.1109/CoG47356.2020.9231692 | - |
Appears in Collections: | Scholarly Works - InsDG |
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Mario_Level_Generation_From_Mechanics_Using_Scene_Stitching_2020.pdf Restricted Access | 674.99 kB | Adobe PDF | View/Open Request a copy |
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