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Estimation Algorithm of Machine Operational Intention by Bayes Filtering with Self-Organizing Map
المؤلفون المشاركون
Suzuki, Satoshi
Harashima, Fumio
المصدر
Advances in Human-Computer Interaction
العدد
المجلد 2012، العدد 2012 (31 ديسمبر/كانون الأول 2012)، ص ص. 1-20، 20ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2012-01-12
دولة النشر
مصر
عدد الصفحات
20
التخصصات الرئيسية
الملخص EN
We present an intention estimator algorithm that can deal with dynamic change of the environment in a man-machine system and will be able to be utilized for an autarkical human-assisting system.
In the algorithm, state transition relation of intentions is formed using a self-organizing map (SOM) from the measured data of the operation and environmental variables with the reference intention sequence.
The operational intention modes are identified by stochastic computation using a Bayesian particle filter with the trained SOM.
This method enables to omit the troublesome process to specify types of information which should be used to build the estimator.
Applying the proposed method to the remote operation task, the estimator's behavior was analyzed, the pros and cons of the method were investigated, and ways for the improvement were discussed.
As a result, it was confirmed that the estimator can identify the intention modes at 44–94 percent concordance ratios against normal intention modes whose periods can be found by about 70 percent of members of human analysts.
On the other hand, it was found that human analysts' discrimination which was used as canonical data for validation differed depending on difference of intention modes.
Specifically, an investigation of intentions pattern discriminated by eight analysts showed that the estimator could not identify the same modes that human analysts could not discriminate.
And, in the analysis of the multiple different intentions, it was found that the estimator could identify the same type of intention modes to human-discriminated ones as well as 62–73 percent when the first and second dominant intention modes were considered.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Suzuki, Satoshi& Harashima, Fumio. 2012. Estimation Algorithm of Machine Operational Intention by Bayes Filtering with Self-Organizing Map. Advances in Human-Computer Interaction،Vol. 2012, no. 2012, pp.1-20.
https://search.emarefa.net/detail/BIM-493558
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Suzuki, Satoshi& Harashima, Fumio. Estimation Algorithm of Machine Operational Intention by Bayes Filtering with Self-Organizing Map. Advances in Human-Computer Interaction No. 2012 (2012), pp.1-20.
https://search.emarefa.net/detail/BIM-493558
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Suzuki, Satoshi& Harashima, Fumio. Estimation Algorithm of Machine Operational Intention by Bayes Filtering with Self-Organizing Map. Advances in Human-Computer Interaction. 2012. Vol. 2012, no. 2012, pp.1-20.
https://search.emarefa.net/detail/BIM-493558
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-493558
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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