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.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Shibasaki H (1974) Attempt toward the standardized interpretation of clinical EEG (in Japanese). Clin Electroencephalogr 16:5
Electric Joint Research (in Japanese) (1979) 35(3):36–41
Popoulis A (1965) Probability, random variables and stochastic processes. McGraw-Hill, Kogakusha, Tokyo
Lighthill MJ (1959) An introduction to Fourier analysis and generalized functions. Cambridge University Press, New York
Goto S, Nakamura M, Nanayakkara N, et al. (1995) Reliable automatic decision making for washing the polluted insulators in coastal substations. Conference on Electrical Insulation and Dielectric Phenomena, Virginia, USA, Oct 22–25, 1995, pp 408–411
Sugi T, Nakamura M, Ikeda A, et al. (1997) Automatic EEG spike detection by use of adaptive decision criteria to individual EEG records. 11th IFAC Symposium on System Identification (SYSID'97), CS20-4, pp 1313–1318
Jasper HH (1958) Report of the commitee on methods of clinical examination in electroencephalography. Electroencephalogr. Clin Neurophysiol 10:370–375
Nakamura M, Shibasaki H, Imajoh K, et al. (1992) Automatic EEG interpretation: a new computer-assisted system for the automatic integrative interpretation of awake background EEG. Electroencephalogr Clin Neurophysiol 82:423–431
Kullback S (1978) Information theory and statistics. Peter Smith, Mass., USA
Zadeh LA (1973) Outline of a new approach to the analysis of complex systems and decision process. IEEE Trans Syst Man Cybern 3:28–44
Shannon CE (1949) The mathematical theory of communication. University of Illinois Press, Champaign
Kobatake H (1987) Optimization of voice/unvoiced decisions in nonstationary noise environments. IEEE Trans Acoustics Speech Signal Process 35:9–18
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Nakamura, M., Goto, S. & Sugi, T. Artificial realization of human on-off decision making based on the conditional probability of a database. Artif Life Robotics 4, 89–95 (2000). https://doi.org/10.1007/BF02480862
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF02480862