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.

Answer Set Programming for Declarative Content Specification: A Scalable Partitioning-Based Approach

Calimeri, Francesco;Germano, Stefano;Ianni, Giovambattista;PACENZA, FRANCESCO;PEZZIMENTI, ARMANDO;Tucci, Andrea
2018

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.
9783030038397
Answer Set Programming; Artificial intelligence in games; Computational intelligence in games; Declarative Content Specification; Game content generation; Procedural content generation; Theoretical Computer Science; Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/290276
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