出版社：Information and Media Technologies Editorial Board
摘要：We investigate an Abductive Logic Programming (ALP) framework to find appropriate hypotheses to explain both professional and amateur skill performance, and to distinguish and diagnose amateur faulty performance. In our approach, we provide two kinds of rules: motion integrity constraints and performance rules. Motion integrity constraints are essential to formulate skillful performance, as they prevent the generation of hypotheses that contradict the constraints. Performance rules formulate the problem of achieving difficult physical tasks in terms of preferred body movements as well as preferred muscles usage and preferred posture. We also formulate the development of skills in terms of default logic by considering the basic skills as defaults, and advanced skills as exceptions. In this case, we introduce preferences in integrity constraints: either hard integrity constraints to be always satisfied or soft integrity constraints which can be ignored if necessary. Finally we apply this framework to realize skill diagnosis.
