Paper Info
Title
Context-aware Bayesian intention estimator using Self-Organizing Map and Petri net
Abstract
For intelligent human-machine systems supporting user's operation, prediction of the user behavior and estimation of one's operational intention are required. However, the same high abilities as human being are required for such intelligent machines since human decides own action using advanced complex recognition ability. Therefore, the present authors proposed a Bayesian intention estimator using Self-Organizing Map (SOM). This estimator utilizes a mapping-relation obtained using SOM to find transition of the intentions. In this paper, an improvement of the Bayesian intention estimator is reported by considering the task context. The scenario of whole task is modeled by Petri net, and prediction of belief in Bayesian computation is modified by other probability estimated from the Petri-Net scenario. Applying the presented method to an estimation problem using a remote operation of the radio controlled construction equipments, improvements of the estimator were confirmed; an undetected intention modes were correctly detected, and inadequate identification was corrected with adequate timing.
Year
DOI
Venue
2011
10.1109/ROMAN.2011.6005232
RO-MAN
Keywords
Field
DocType
belief networks,petri nets,radio controlled construction equipments,user interfaces,som,self-organizing map,intelligent human-machine systems,ubiquitous computing,petri net,self-organising feature maps,advanced complex recognition ability,context-aware bayesian intention estimator,probability,human machine interface,estimation,indexes,indexation,probabilistic logic,scientific research,prediction algorithms,computer supported cooperative work,mathematical model
Remote operation,Petri net,Computer science,Self-organizing map,Artificial intelligence,Probabilistic logic,User interface,Invariant estimator,Machine learning,Estimator,Bayesian probability
Conference
ISBN
Citations 
PageRank 
978-1-4577-1572-3
0
0.34
References 
Authors
3
2
Name
Order
Citations
PageRank
Satoshi Suzuki139433.37
Fumio Harashima216825.48