Users’ Evaluation of Procedurally Generated Game Levels

Galdieri, Riccardo; Longobardi, Alessandro; Bonis, Michele De; Carrozzino, Marcello

doi:10.1007/978-3-030-87595-4_4

Cited by 2 publications

(3 citation statements)

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“…Although there has been a peak in research on this topic, a recent study from Galdieri et al [19] concluded, through a user study, that procedural level generation involves many risks and may even affect the users' satisfaction, leading to a decrease in the sales number and profit margin, which is what moves the industry. Their study was applied to a research puzzle game called EscapeTower, developed in the authors' previous studies.…”

Section: Academic Workmentioning

confidence: 99%

“…Besides the work from Galdieri et al [19], other works have been proposed over the years in the field of Game Adaptivity, most using PCG. An example is Game-O-Matic, from Treanor et al [59], which aims at generating whole games according to ideas described by users.…”

Section: Academic Workmentioning

confidence: 99%

“…Regarding JS, some browsers, such as Mozilla Firefox, do not run at the specified frame rate (30 frames per second). The low performance in these browsers can affect the players' experience, especially since it is a popular browser nowadays, and 37 out of 189 testers, i.e., 19.6% of the population, used it in the second prototype. Some users even commented on this lack of performance, stating that "the game runs really poorly," and asking to "increase the framerate.…”

Section: Infinite Mario Brosmentioning

confidence: 99%

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Exploring Player Adaptivity through Level Design: A Platformer Case Study

Esteves

Jacob

Rodrigues

2022

2022 International Conference on Graphics and Interaction (ICGI)

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Different people experience distinct feelings while playing the same game. For instance, some players like action-heavy games, while others prefer puzzles. Creating a game that engages everyone is not trivial and, ultimately, impossible. However, generating content adapted to the players could improve their experience, thus maximizing the potential player base.Therefore, a game designer's role can be challenging when dealing with games with static content. With adaptive games, these can be designed to act differently according to several actions without developing different versions. Although this approach seems to solve all the designers' problems, creating these games can be very time-consuming, increasing the development time and budget. Besides, creating a generic approach that adapts content for every game genre or even different games inside the same genre is not trivial.To tackle this problem, this work proposes a methodology to explore player adaptivity through level design that follows three phases: (i) the selection of a genre and a game, (ii) a first study to correlate players' profiles, preferences, and actions with single elements, and (iii) a second study, based on the previous, to evaluate the impact of generating and adapting game levels.Using a version of a well-known platform game, Super Mario Bros., the first results show it is not possible to correlate players' profiles with game elements. However, several preferences for levels with specific configurations were spotted and used for the second study's adaptation. Nevertheless, these adaptations did not sufficiently impact the players' overall experience in the second study.Although the results do not seem encouraging, other deeper analyses of the study's data should be performed in the future using distinct algorithms and machine learning. Moreover, the same methodology should be applied to other games to ensure similar results are obtained. Last but not least, a study should be conducted to explore correlations between players' profiles and groups of game elements, especially obstacles around gaps.

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Section: Academic Workmentioning

confidence: 99%

Section: Academic Workmentioning

confidence: 99%

Section: Infinite Mario Brosmentioning

confidence: 99%

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