Using gameplay semantics to procedurally generate player-matching game worlds

Lopes, Ricardo; Tutenel, Tim; Bidarra, Rafael

doi:10.1145/2538528.2538531

Cited by 11 publications

(12 citation statements)

References 17 publications

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“…To the best of our knowledge, there has been no research on enabling game designers to combine player modeling and content generation to author adaptive games in an interactive fashion. Previously, the use of gameplay semantics as a suitable vocabulary to support the control over PCG methods and its integration with player modeling techniques has been proposed [19]. We believe that our approach, together with current research advancements in PCG and player modeling, already provides a mature basis to start incorporating designers as active agents in the adaptive game creation loop.…”

Section: Related Workmentioning

confidence: 99%

“…Skill profiles take the role of the preconditions of a semantic gameplay description, and content descriptions take the role of the semantics classes of a description. These semantic gameplay descriptions (now adaptation rules) are created directly by designers, and are not automatically derived from classes labeled with gameplay semantics, like in previous work [19], [21], [22].…”

Section: A Adaptation Rulesmentioning

confidence: 99%

“…Similarly to previously-proposed semantic gameplay descriptions [19], adaptation rules are solutions, outlined by designers, for a class of adaptation problems. For adaptation rules to work, two tasks have to be performed: (i) identify in which circumstances they apply, and (ii) trigger the creation of an appropriate set of game content.…”

Section: B Rule Matching and Retrievalmentioning

confidence: 99%

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Authoring Adaptive Game World Generation

2018

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Current research on adaptive games has mainly focused on adjusting difficulty in a variety of ways, for example, by providing some control over adaptive game world generation. These methods, however, are mostly ad-hoc and require quite some technical skills. To the best of our knowledge, so far there has been no adaptive method that is truly generic and explicitly designed to actively include game designers in the content creation loop. In this article, we introduce a generic method that enables designers to author adaptivity of game world generation, in a very expressive and specific fashion. Our approach uses adaptation rules which build atop gameplay semantics in order to steer the on-line generation of game content. Designers create these rules by associating skill profiles, describing skill proficiency, with content descriptions, detailing the desired properties of specific game world content. This game content is then generated on-line using a rule matching and retrieval approach. We performed user studies with both designers and players, and concluded that adaptation rules provide game designers with a rich expressive range to effectively convey specific adaptive gameplay experiences to players.

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Section: Related Workmentioning

confidence: 99%

Section: A Adaptation Rulesmentioning

confidence: 99%

Section: B Rule Matching and Retrievalmentioning

confidence: 99%

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Authoring Adaptive Game World Generation

2018

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“…As a result, PCG control is evolving towards more natural and high-level interaction between designer and machine, with the use of techniques like declarative modeling [29,10], controllable agents [5] and gameplay-based control [14].…”

Section: Chaptermentioning

confidence: 99%

Constructive generation methods for dungeons and levels

Shaker

Liapis

Togelius

et al. 2016

Procedural Content Generation in Games

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“…Dormans and Bakkes [20], [28] investigated the procedural generation of entire levels for action-adventure games, which distinguishes between missions and spaces as two separate structures that need to be generated in two individual steps. Lopes et al [29] developed a framework aimed at creating personalised content for complex and immersive game worlds; by modelling which content provided the context for a given personal gameplay experience. Sorenson et al [30] developed an approach to automatic video game level design consisting of a computational model of player enjoyment and a generative system based on evolutionary computing.…”

Section: Space Adaptationmentioning

confidence: 99%

Challenge balancing for personalised game spaces

Bakkes

Whiteson

et al. 2014

2014 IEEE Games Media Entertainment

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Challenge Balancing for Personalised Game SpacesBakkes, S.C.J.; Whiteson, S.A.; Li, G.; Viniuc, G.V.; Charitos, E.; Heijne, N.; Swellengrebel, A. General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Abstract-In this paper we propose an approach for personalising the space in which a game is played (i.e., levels) -to the end of tailoring the experienced challenge to the individual user during actual play of the game. Our approach specifically considers two design challenges, namely implicit user feedback and high risk of user abandonment. We contribute an approach that acknowledges that for effective online game personalisation, one needs to (1) offline learn a policy that is appropriate in expectation across users -to be used for initialising the online game, (2) offline learn a mapping from gameplay observations to the player experience -to be used for guiding the online game personalisation, and (3) rapidly converge to an appropriate policy for the individual user in online gameplay -employing the learned feedback model and a straightforward model of user abandonment. User studies that validate the approach to online game personalisation in the actual video game INFINITE MARIO BROS. indicate that it provides an effective basis for automatically balancing the game's challenge level to the individual human player.

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Using gameplay semantics to procedurally generate player-matching game worlds

Cited by 11 publications

References 17 publications

Authoring Adaptive Game World Generation

Authoring Adaptive Game World Generation

Constructive generation methods for dungeons and levels

Challenge balancing for personalised game spaces

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