Jaekoo Joo

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Complex cognitive processes corresponding to human control behaviors cannot be easily inferred using (1) a logical rule-based model, (2) a statistical model, or (3) an analytical predictive model. Predicting human behaviors in complex and uncertain environments like emergency evacuation is considered almost impossible (at least NP hard) in systems theory.(More)
We propose a predictive modeling framework for human-involved complex systems in which humans play controlling roles. Affordance theory provides definitions of human actions and their associated properties, and the affordance-based Finite State Automata (FSA) model is capable of mapping the nondeterministic human actions into computable components in(More)
Although feature-based computer-aided process planning plays a vital role in automating and integrating design and manufacturing for ef®cient production, its off-line properties prohibit the shop ¯oor controllers from rapidly coping with unexpected production errors. The objective of the paper is to suggest a neural network-based dynamic planning model, by(More)
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