Using Hidden Markov Model Learning to Redress the Attention Deficit in Autistic Children

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Research areas:
Year:
2015
Type of Publication:
Article
Keywords:
Autistic Children, Hidden Markov Model, Pavlovian Learning, Reinforcement Learning
Authors:
Sara Motamed; Saeed Setayeshi; Elham Askari; Zeinab Farhoudi
Journal:
IJAIM
Volume:
3
Number:
4
Pages:
223-226
Month:
Jan.-Feb.
ISSN:
2320-5121
Abstract:
This paper introduces an effective model to solve the problem of shift attention and focus attention in autistic children. The proposed model inspired by model of brain decision and it consists of three hierarchical parts: Preprocessing, shift attention and focus attention. Each part has an important role to find the autistic children problems. Hidden Markov Model (HMM) is used to solve the problem of focus attention and Pavlovian learning is used to solve the problem of shift attention. Finally, the proposed model has been compared with different models of learning. Experimental results show that the proposed model has the higher performance on unpredictable or chaos situations
Full text: IJAIM-319_final.pdf

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