Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/82027
Title: | Mario level generation from mechanics using scene stitching |
Authors: | Cerny Green, Michael Mugrai, Luvneesh Khalifa, Ahmed Togelius, Julian |
Keywords: | Computer games -- Design Artificial intelligence |
Issue Date: | 2020 |
Publisher: | Institute of Electrical and Electronics Engineers |
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. |
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. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/82027 |
Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Mario_Level_Generation_From_Mechanics_Using_Scene_Stitching_2020.pdf Restricted Access | 674.99 kB | Adobe PDF | View/Open Request a copy |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.