Abstract
Procedural Content Generation is applied in the development process of many commercial games: automatically generated game contents are delivered to players in order to offer a constantly changing user experience and enrich the game itself. Usually, the generative process relies on search-based non-deterministic algorithms, which encode one or more techniques for guaranteeing “legal” yet diversified output. Declarative approaches to content generation, more properly defined as Declarative Content Specification techniques, like the ones based on Answer Set Programming, allow to focus on describing content requirements rather than programming ad-hoc generation engines, and to fast prototype generation techniques themselves. This work investigates to what extent ASP-based DCS is scalable enough for industrial contexts, by proposing a partitioning-based approach. A working prototype, available as an Unity Asset and as a GVGAI framework level generator is presented.
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10 January 2019
The original version of the paper “Answer Set Programming for Declarative Content Specification: A Scalable Partitioning-Based Approach” starting on p. 225 has been revised.
Notes
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The reader can refer to the last edition of [20] for a comprehensive survey of generation techniques and related research.
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Calimeri, F., Germano, S., Ianni, G., Pacenza, F., Pezzimenti, A., Tucci, A. (2018). Answer Set Programming for Declarative Content Specification: A Scalable Partitioning-Based Approach. In: Ghidini, C., Magnini, B., Passerini, A., Traverso, P. (eds) AI*IA 2018 – Advances in Artificial Intelligence. AI*IA 2018. Lecture Notes in Computer Science(), vol 11298. Springer, Cham. https://doi.org/10.1007/978-3-030-03840-3_17
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