Decision Complexity and Methods to Meet Them

N. C. Das ()
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N. C. Das: Birsa Agricultural University, Department of Statistics

Chapter Chapter 2 in Decision Processes by Using Bivariate Normal Quantile Pairs, 2015, pp 19-45 from Springer

Abstract: Abstract In this chapter, components of decision complexity can be seen as a tetrahedral structure with complexity as vertex in third dimension. Its base is a triangle with three vertices V 1, V 2 and V 3 (see Fig. 2.1). V 1 represents the vertex of uncertainty, its conception and developments through the ages from the Vedic to the present era. These have been dealt within Sects. 2.2, 2.3, 2.4 and 2.5, which provide a genesis for such developments. The next component of complexity represented by the vertex V 2 is dependence, which has been discussed in Sects. 2.6, 2.7, 2.8, 2.9, 2.10, 2.11, 2.12 and 2.13. Mankind’s awareness of its existence and the methodologies employed to explore and circumvent it have also been traced right from the Vedic and the post-Vedic era. However, only such methods have been mentioned which are popularly known and have been applied frequently and widely by empirical scientists. The third and the last component of complexity, that is dynamism, has been represented as the vertex V 3, the apex vertex of the base triangle of that tetrahedral structure, representing decision complexity. It has been summarized in Sects. 2.14, 2.15, 2.16 and 2.17, only to assert that mankind has been quite progressive on this front also, even though it has been relatively difficult to explore this aspect. This area has been difficult and is dependent on the developments in other areas. Advancements made in this field are relatively recent. Hence, they have found fewer applications, in spite of their prospective use in predictive modelling, essential in decision-making processes.

Keywords: Action calculus; Adaptive decision; Bayesian inference; BIVNOR; Branching process; Complexity components; Causal algebra; Causal calculus; Equi-quantile value; Info-acquirers; Predictive distribution; Ramsalaka-prashnavali; Transitive causation; Stochastic independence (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-81-322-2364-1_2

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