Abstract
Applied Behavior Analysis-based early interventions are evidence based, efficacious therapies for autism. They are, however, labor intensive and often inaccessible at the recommended levels. In this paper we present ongoing doctoral research aimed at development of the formal, computational representation for Applied Behavior Analysis (ABA) that could serve as a reasoning foundation for intelligent-agent mediated ABA therapies. Our approach is to formulate the representation of ABA dynamics and concepts as a process ontology expressed in a controlled natural language (CNL). As an ontology language, CNL is not only a machine interpretable, logically sound reasoning foundation, but also understandable and editable by human users.
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Begoli, E., Ogle, C.L., Cihak, D.F., MacLennan, B.J. (2013). Towards an Integrative Computational Foundation for Applied Behavior Analysis in Early Autism Interventions. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds) Artificial Intelligence in Education. AIED 2013. Lecture Notes in Computer Science(), vol 7926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39112-5_138
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DOI: https://doi.org/10.1007/978-3-642-39112-5_138
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