Crossover of Affective Artificial Intelligence Between Robotics Simulator and Games

Abstract

The aim of this paper is to share state of the art in the field of robotics and artificial intelligence from one side and gaming from other side. Inspired from affective computing in social robotics and in order to improve the learning factor of serious games, we introduce an affection layer which improves the emotional intelligence of a game character. As the components of that layer we propose modules which can be integrated in a game engine in order to enhance the verisimilitude of the virtual world. The proposed architecture can be integrated in several games to improve their emotional abilities which can lead to developing believable characters in the game environment. We believe that such ability increase the motivation for the user to learn since possibilities and situations would be much pragmatic.