An Emerging Serious Game Engine with a Parameter Adaptive System based on an evolutionary approach

Abstract

In this work is proposed a parameter adaptive system for emerging serious games, which allows the emerging of properties in a game, in order to adapt it to the educational context in which it is being used. Previous articles have proposed an engine for emerging serious games based on the ant colony optimization algorithm, which allows the initial emergence of a serious game. In this paper, another component of the game adaptive sub-system of the engine is specified, which allows its dynamic adaptation while the game is running, in this case, in order to adapt its properties to the educational context-domain. Particularly, the property emergence system is based on the use of cultural algorithms, which establishes a learning process to modify its parameters. This system is tested in the context of a smart classroom.