Download Intelligent Decision-making Support Systems: Foundations, by Jatinder N.D. Gupta PDF

By Jatinder N.D. Gupta

This e-book may be got by way of researchers and graduates scholars in synthetic Intelligence and administration in addition to training managers and experts drawn to the appliance of IT and knowledge platforms in actual enterprise environment.

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Additional resources for Intelligent Decision-making Support Systems: Foundations, Applications and Challenges (Decision Engineering)

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A. Forgionne, L. D. , New York, NY. , New York, NY. Boering E (1933) The Physical Dimensions of Consciousness. New York: Century. Borenstein D (1998) IDSSFLEX: an intelligent DSS for the design and evaluation of flexible manufacturing systems. Journal of the Operational Research Society 49(7): 734-744. Brooks F (1996). The computer scientist as toolsmith II. Communications of the ACM, 19(3): 61-68. Brown C, O’Leary D (1995) Introduction to Artificial Intelligence and expert systems. htm, on September 15, 2004.

In the first studies on “Human Problem Solving”, which are recorded in the seminal book of Newell and Simon (1972), decision making is intertwined with heuristic search. The first intelligent problem solver, namely GPS (see Newell and Simon 1963, Newell and Simon 1972), was created on the principle of recursive difference reduction. 1). The core principle of a heuristic search is to make the decision about the "best intermediary sub-goal". 2): • • • develop, i. e. search new sub-goals along the same path for further reducing the difference without changing the current state; backtrack, i.

Philips-Wren, M. A. Forgionne, L. D. Gupta intelligence embedded in the algorithms or processing mechanisms of a particular DMSS. It must be noted that any support level includes or can include capabilities from previous levels. Hence, we claim that this framework is useful to analyze the support capabilities of past, current, and future DMSS such as i-DMSS. 1 (Forgionne et al. 2002)illustrates an example of how these capabilities could be implemented. Computational power and memory are needed to access and analyze massive data, and AI techniques are needed to develop the intelligent behaviors needed for complex decision-making situations.

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