Artificial realization of human on-off decision making based on the conditional probability of a database
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Abstract
As human on-off decisions are the basic problems in our human lives, the analysis of human on-off decision making is an interesting topic. The procedures of qualified human decision making include many intuitive factors which have been acquired from previous valuable experience and gained through learning, but they may not be easily understood by others within a short period. By the use of a database of causes and decisions made by qualified experts for an objective event, human decision making for that event can be realizable artificially. This paper investigates a general method for realizing artificial human on-off decision making based on the conditional probability of the database. As on-off decision making is a discrete event and the causes for that decision making are continuous events, a mathematical treatment of a Dirac delta function in a probability density function is required to derive the conditional probability for the decision making. Several examples of artificial human decision making by the proposed method were demonstrated, and the results obtained showed good agreement with those of human experts in the respective fields.
Key words
On-off human decision making Artificial realization of human decisions Conditional probability Data-base Insulator washing timing Spike detectionPreview
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