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Introduction

  • Sisir RoyEmail author
Chapter

Abstract

The purpose of the decision-making process is to determine the results while committing a categorical statement or proposition. A statement or proposition is a sentence which is either true or false. A categorical proposition or statement relates two classes or categories. This process is used widely in many disciplines, for example, in complex scientific, engineering, economical, and management situations. It is necessary to consider all possible rational, heuristic, and intuitive selections so that we can summarize the results in arriving at a decision. The diversified and broad range of interests for understanding this process have induced scientific researcher also to employ a diverse and broad range of research methodologies. They began by exploring other related but independent avenues of thinking, for example, taking into account the many methods of empirical observations, together with developing essentially-related mathematical analysis, including many kinds of computational modelling. Following this mode of search, it would be possible, theoretically, to identify a method for making crucial observations. In turn, its consequences continue to enrich philosophical discourses and to further fragment decision research. Many major attempts have been made to develop independent perspectives connected to various frameworks, such as; game theory, Bayesian models, and expected utility models; models connected to behavioral decision; and approaches related to information processing for neural networks and cognitive architectures. It has already been recognized that axiomatic, as well as other kind of rigorous models of the cognitive decision making, are very much needed. The recent empirical findings in the cognitive domain clearly suggest the necessity of changing the paradigm from classical Bayesian probability theory to quantum probability to construct the model of decision making in a consistent manner. However, quantum probability is an extension of quantum logic which only incorporates the contradictions arising out of the simultaneous existence of two mutually exclusive events in a logical way rather than discarding them. It gives rise to a new possibility to model certain degrees of contradictions involved in emotions, as well as to quantify the effect of emotions on judgments and decision making.

Keywords

Bayesian probability Quantum probability Empirical evidence Normative models Human cognition Axiomatic approach Fisher information Emotions Affective computation Quantum logic 

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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.National Institute of Advanced Studies, IISc CampusBengaluruIndia

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