DIMACS TR: 2000-24

Question-Answering System for Teaching Autistic Children to Reason about Mental States

Authors: Boris Galitsky


We build the natural language question-answering system to teach autistic patients reasoning about mental states. In accordance to our model of autism disorder, some reasoning patterns concerning perception of the concepts of knowing, believing and intention are corrupted. Based on this model, we have suggested the autism diagnosis and reasoning rehabilitation strategy, where the professional psychologists explained the autistic children the set of multi-agent scenarios. Experiments showed that acquiring of mental concepts based on our formalism helps autistic children not only to improve judgment interacting with other people, but also to stimulate the emotional development.

Further evaluation of the model and rehabilitation technology is conducted with automatic training toolkit, implemented on the Internet. Asking questions about mental states of heroes of the scene or textual scenarios assists the revealing and training of the corrupted autistic reasoning. Natural language technology of semantic headers is applied, where the textual answer (explanation) is assigned with a mental formula, which is matched against the representation of an input question or command.

Paper Available at: ftp://dimacs.rutgers.edu/pub/dimacs/TechnicalReports/TechReports/2000/2000-24.ps.gz
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