Adaptive System for the Generation of Emerging Behaviors in Serious Emerging Games

Authors

  • José Aguilar Universidad de los Andes, Facultad de Ingeniería; Universidad EAFIT
  • Junior Altamiranda Universidad de los Andes, Facultad de Ingeniería
  • Francisco Díaz Universidad EAFIT

DOI:

https://doi.org/10.13053/cys-24-3-3180

Keywords:

Serious emerging games, serious emerging game engine, video game adaptation system, smart classroom, fuzzy classifier system, cultural algorithms, ant colony optimization algorithm

Abstract

A video game adaptation system (SAV) for serious emergent games (JSE), allows emergent behaviors in the game, such as the appearance of environments, events, narratives and characters, among others, in order to adapt to the context in the one that is developing. In previous articles the architecture of a JSE engine has been proposed. Furthermore, a first subsystem has been proposed that allows the emergence of a JSE according to the objectives of the environment, based on the ant colony optimization algorithm (ACO). In the present work, the second component of said architecture is specified, the SAV, which allows its dynamic adaptation (during the JSE). The SAV is made up of the sub-layers of strategies, sequences and properties, which manage each of these types of possible emergencies in a JSE, with the intention of dynamically adapting it to the context-domain where the game is being played. Furthermore, in this work the behavior of these sublayers is analyzed in a specific case study, showing very encouraging results of SAV in the educational context of an intelligent classroom (SaCI).

Author Biographies

José Aguilar, Universidad de los Andes, Facultad de Ingeniería; Universidad EAFIT

Full Professor

Junior Altamiranda, Universidad de los Andes, Facultad de Ingeniería

Full Professor

Francisco Díaz, Universidad EAFIT

PhD Student

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Published

2020-09-29

Issue

Vol. 24 No. 3 (2020): 24(3) 2020

Section

Articles

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