Intelligent Decision Support Machines For Business Decisions

  • Hans W Gottinger STRATEC Munich Germany
  • STRATEC Munich

Abstract

An intelligent decision support machine (IDSM) is a computer-based interactive tool of decision making for well-structured decision and planning situations that uses jointly decision-theoretic methods and machine learning techniques with access to structured data bases. An IDSM emerges from a model based system underlying a decision model (under uncertainty) imposing a normative (prescriptive ) structure of decision making.

In the past years there has been substantial attention devoted to the use of artificial intelligence (AI) techniques, first most commonly rule-based expert systems, more recently methods of machine learning as tools for decision support. Based on those rules we design a machine learning algorithm guiding through principles of an IDSM.

References

(1) Bush,R.R. and Mosteller, F.(1955),Stochastic Models for Learning, John Wiley: New York

(2) Cohen, P. R. (1985) Heuristic Reasoning about Uncertainty: An Artificial Intelligence Approach, Pitman, London.

(3) Fishburn, P. C. (1988) Nonlinear Preference and Utility Theory, The Johns Hopkins Univ. Press: Baltimore, MD.

(4) Gershman,S.J., Horvitz,E.J. and Tenenbaum,J.B. (2015), “Converging Rationality: A converging paradigm for intelligence in brains, minds and machines”, Science Magazine 349(6245), July 17, 273-278

(5) Gottinger,H.W and Weimann,P. (1990), Artificial Intelligence, A Tool for Industry and Management , Ellis Horwood: Chichester, Sussex, England

(6) Gottinger,H.W.(2017), Internet Economics: Models, Mechanisms and Management, Bentham Science: London

(7) Holtzman, S. (1989) Intelligent Decision Systems, Addison-Wesley: Reading, Mass.

(8) Howard, R. A. and Matheson, J. E. (1981) “Influence Diagrams”, 1981, In: Howard, R. A. and J. E. Matheson (eds), The Principles and Applications of Decision Analysis, SDG Publications, Strategic Decisions Group: Menlo Park, California, 1984.

(9) Parkes,D.C. and Wellman,M.P.(2015), “Economic Reasoning and Artificial Intelligence”, Science Magazine 349(6245), July 17, 273-278

(10) Pearl, J. (1988) Probabilistic Reasoning in Intelligent Systems, Morgan Kaufmann: Los Altos, Ca.

(11) Davis, R. (2016) Neural Networks and Deep Learning Explained, AWS: London

(12) Savage, L. J. (1954) The Foundations of Statistics, Wiley

Publications: New York.

(13) Shachter, R. D. (1986) ‘Evaluating Influence Diagrams’, Operations Research 34.

Published
2018-05-03
How to Cite
Gottinger, H. W., & Munich, S. (2018). Intelligent Decision Support Machines For Business Decisions. Transactions on Machine Learning and Artificial Intelligence, 6(2), 10. https://doi.org/10.14738/tmlai.62.4372