This paper presents an adaptive architecture for educational games which are evolved and optimized in order to fulfill the educational goals while reflecting the specific requirements and features of the user community. The approach is based on an online genetic framework where typical genetic operators like crossover and mutation are designed to evolve a population of games, and the online fitness driving the evolution is given by a metric of user behavior/performance, evaluated on the actual community of users. The evolutionary structure adapt can also be applied for continuous game adaptation in dynamical domains where the user community and/or the educational goals are changing over the time.
Community Adaptive Educational Games
MILANI, Alfredo;
2011-01-01
Abstract
This paper presents an adaptive architecture for educational games which are evolved and optimized in order to fulfill the educational goals while reflecting the specific requirements and features of the user community. The approach is based on an online genetic framework where typical genetic operators like crossover and mutation are designed to evolve a population of games, and the online fitness driving the evolution is given by a metric of user behavior/performance, evaluated on the actual community of users. The evolutionary structure adapt can also be applied for continuous game adaptation in dynamical domains where the user community and/or the educational goals are changing over the time.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
