In the context of video games, Procedural Content Generation (PCG) refers to the automatic creation of contents, performed using algorithms and/or heuristics that are generally designed specifically for the game under development. PCG can be exploited to produce different contents, depending on the video game genre and on the peculiarities of the specific game, with the positive effects of reducing development time and increasing randomness of content and/or gameplay. In this invited speech, we present some resent researches on Experience Driven PCG (EDPCG) conducted in the PONG (Playlab fOr inNovation in Games) laboratory of the Department of Computer Science at University of Milan. In particular, we have presented two different examples showing the need of an accurate design of EDPCG, which requires the acquisition of data for a profiling of the player characteristics. Moreover, because EDPCG is based on the adaptation of specific game content to the player profile, we have shown an innovative approach, based on the application of a Genetic Algorithm, for the procedural generation of 3D models, using parametric curves. With this approach, we can have a fine control in the generation of dynamic meshes, based on a limited set of parameters.
An(other) overview of Procedural Content Generation Techniques applied to Game Design and Development (Keynote Speech) / D. Gadia. ((Intervento presentato al 22. convegno GAME‐ON : European Conference on Simulation and AI in Computer Games tenutosi a Aveiro nel 2021.
An(other) overview of Procedural Content Generation Techniques applied to Game Design and Development (Keynote Speech)
D. GadiaPrimo
2021
Abstract
In the context of video games, Procedural Content Generation (PCG) refers to the automatic creation of contents, performed using algorithms and/or heuristics that are generally designed specifically for the game under development. PCG can be exploited to produce different contents, depending on the video game genre and on the peculiarities of the specific game, with the positive effects of reducing development time and increasing randomness of content and/or gameplay. In this invited speech, we present some resent researches on Experience Driven PCG (EDPCG) conducted in the PONG (Playlab fOr inNovation in Games) laboratory of the Department of Computer Science at University of Milan. In particular, we have presented two different examples showing the need of an accurate design of EDPCG, which requires the acquisition of data for a profiling of the player characteristics. Moreover, because EDPCG is based on the adaptation of specific game content to the player profile, we have shown an innovative approach, based on the application of a Genetic Algorithm, for the procedural generation of 3D models, using parametric curves. With this approach, we can have a fine control in the generation of dynamic meshes, based on a limited set of parameters.Pubblicazioni consigliate
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