Agent-Based Personalisation and User Modeling for Personalised Educational Games

Personalisation can increase the learning efficacy of educational games by tailoring their content to the needs of the individual learner. This paper presents the Personalised Educational Game Architecture (PEGA). It uses a multi-agent organisation and an ontology to offer learners personalised training in a game environment. The multi-agent organisation's exibility enables adaptive automation; the instructor can decide to control only parts of the training, while leaving the rest to the intelligent agents