Ongoing work: Study of improving Active Preference Learning and application on the context of immersive wheelchair simulator

On the basis of the current development of active preference learning, we are trying to extend the algorithm in such a way that can exploit more information from users from asking suitable questions to modifying available algorithm in such a way that helps to find the optimal set of parameter faster than the currently available algorithm. The designed algorithm is then applied to the work of RIENTR@ project for validation.