Title | ||
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Transposition Of Location-Based Games: Using Procedural Content Generation To Deploy Balanced Game Maps To Multiple Locations |
Abstract | ||
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Location-Based Games (LBGs) rely on the player's location to change its game state. Developing worldwide LBGs is a challenging task due to the need to deploy game instances in multiple locations, while maintaining the same game balancing, features, and even correlations between locations of the game and the real world. Hence, it is virtually impossible to manually design interactions, challenges, and game scenarios for every place a player is at. As a result, even modern LBGs still present huge balancing differences between regions and avoid exploring the competition between players like other game genres. This work uses Procedural Content Generation to transpose maps of LBGs while focusing on maintaining their game balancing. We convert LBGs into a game model based on a directed weighted graph using information about Points-of-Interest (POIs) around the players' location. This game model is simplistic and lightweight, which makes it suitable to wearable and IoT devices that are becoming popular among LBGs. Moreover, we use a Genetic Algorithm to generate a corresponding LBG instance with similar game balancing. To validate the proposed approach, we designed four LBGs with distinct features, gameplay, and mechanics, and conducted an experiment that required samples to compare maps generated by the algorithm in different locations. Results indicate that games with similar game balancing score higher and that the number of POIs has a significant impact on the performance of the approach. Finally, we can conclude that this work contributes to improving the development of LBGs by helping to mitigate the challenge of transposing LBGs while maintaining game balancing. (C) 2020 Elsevier B.V. All rights reserved. |
Year | DOI | Venue |
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2021 | 10.1016/j.pmcj.2020.101302 | PERVASIVE AND MOBILE COMPUTING |
Keywords | DocType | Volume |
Location-based Games, Procedural Content Generation, Graph isomorphism | Journal | 70 |
ISSN | Citations | PageRank |
1574-1192 | 0 | 0.34 |
References | Authors | |
0 | 3 |
Name | Order | Citations | PageRank |
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Luís Fernando Maia | 1 | 0 | 0.34 |
Windson Viana | 2 | 201 | 28.40 |
Fernando Trinta | 3 | 39 | 14.93 |