Title :
Bayesian network modeling of operator´s intent inference
Author :
Hatakeya, N. ; Furuta, K.
Author_Institution :
Syst. Sci. Dept., Tokyo Univ., Japan
Abstract :
While human ability has not changed within limitations, machine systems have become more complicated. Humans, therefore, developed automation systems, but this caused human errors in some situations. We need the intent inference method in order to solve these problems because intent inference is an important element of proposing system information optimally. In this paper, we propose an intent inference method. Our model contains intent inference using the whole recognition process and we use a Bayesian network (BN) as inference engine. We conducted experiments and extracted knowledge that is needed to construct BN and compare this result with the simulation result.
Keywords :
belief networks; human factors; inference mechanisms; knowledge acquisition; Bayesian network modeling; OR relation; automation systems; cognitive science; human ability; human engineering; human error; knowledge extraction; noisy-OR relation; operator´s intent inference; recognition process; Acceleration; Automation; Bayesian methods; Cognition; Cognitive science; Data mining; Engines; Ergonomics; Humans; Man machine systems;
Conference_Titel :
Human Factors and Power Plants, 2002. Proceedings of the 2002 IEEE 7th Conference on
Print_ISBN :
0-7803-7450-9
DOI :
10.1109/HFPP.2002.1042847