Humanoid Knowledge-Based Decision Support Systems (KBDSS) – Subjective or Objective Data Query

Ulrich H. Langanke

doi:10.20965/jaciii.2009.p0010

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JACIII Vol.13 No.1 pp. 10-15

doi: 10.20965/jaciii.2009.p0010

(2009)

Paper:

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Humanoid Knowledge-Based Decision Support Systems (KBDSS) – Subjective or Objective Data Query

Ulrich H. Langanke

Budapest Tech, Institute of Intercultural Communication, H-1087 Budapest, Hungary

Received:

November 28, 2007

Accepted:

May 6, 2008

Published:

January 20, 2009

Keywords:

autopoietic, cognition, fuzzy sets, internal representation, neural data processing

Abstract

“Decision” as a cognitive phenomenon can be interpreted as the result of neural behavior. Various scientific models have ever since dealt with this essential aspect of human interaction, involving different philosophic backgrounds such as holistic vs. analytic approaches, Aristotle vs. Confucius, Confucius vs. Buddha with their respective impact on the definition of “subjectivity” and “objecitiviy.” This paper fosters three appoaches for subjective and/or objective decision making: 1) Explained neurobiologically as an internal representation or 2) “autopoietically” according to Radical Constructivism and 3) mathematically as a Fuzzy algorithm. In order to choose the appropriate computational decision support techniques the structural complexity of the phenomenon “decision” has to be determined. Globalization with its manyfold cross-cultural contacts may serve as an example for the relevance of the implementation of KBDSS in real-life settings. When it comes to cross-cultural exchange, business or otherwise, skills in decision making are a cue value and a key to success. The main issue of this paper is to develop a multidisciplinary humanoid approach to the configuration of KBDSS that enable us to follow the traces and identify the origins – neural, sensual, linguistc or other – that are implicitely or explicitely involved in human decision making.

Cite this article as:

U. Langanke, “Humanoid Knowledge-Based Decision Support Systems (KBDSS) – Subjective or Objective Data Query,” J. Adv. Comput. Intell. Intell. Inform., Vol.13 No.1, pp. 10-15, 2009.

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References

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

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[8] [8] R. Fullér, “Introduction to Neuro-Fuzzy Systems,” Heidelberg: Physica-Verlag, 2000.

[9] [9] D. J. Power, “Decision support systems: concepts and resources for managers,” Westport, Conn.: Quorum Books, 2002.

[10] [10] D. C. Armenis and A. Neal, “Recognizing Potential: A Naturalistic Investigation of Employee Promotion Decisions,” J. of Cognitive Engineering and Decision making, 2-1, 63-87, 2008.

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[12] [12] B. Kosko, “Fuzzy Thinking. The New Science of Fuzzy Logic,” London: Harper Collins Publishers, 1994.

[13] [13] Bryant, David J. and Bruyn Martin, Lora et al., “Development and Evaluation of an Intuitive Operational Planning Process,” J. of Cognitive Engineering and Decision Making, 1-4, 434-460, 2007.

[14] [14] H. R. Maturana and F. J. Varela, “Der Baum der Erkenntnis. Die biologischen Wurzeln menschlichen Erkennens,” Bern/München: Scherz Verlag, 1987.

[15] [15] E. R. Kandel and J. H. Schwartz et al., “Essentials of neural science and behavior,” Stamford, Conn.: Prentice Hall International/Appleton & Lange, 1995.

[16] [16] D. J. Power, “Decision support systems: concepts and resources for manager,” Westport, Conn.: Quorum Books, 2002.