Logical Reasoning Decision-Making Practice Sets pdf For all Competitive Exams
Logical Reasoning Approaches Logical reasoning is an essential component of an intelligent system. It acts as a “brain” behind the decision-making process of the system
Logical reasoning techniques rely heavily on the mathematical analysis of historical data (i.e. prior knowledge or experience), from simple probability calculation to more complex calculation such as the Bayesian method and Nash equilibrium
In fact, these techniques have been translated into well-established data mining methods for knowledge discovery, particularly in the field of neural networks. The incorporation of these techniques has led to the formation of a self-learning capability in an intelligent system as it learns via a repetitive process of past experience
Most intelligent systems have some form of decision-making mechanisms built into their organizations. These normally include a logical reasoning element in their design. This paper reviews and compares the different logical reasoning strategies, and tries to address the accuracy and precision of decision making by formulating a tolerance to imprecision view which can be used in conjunction with the various reasoning strategies
Caution to be taken:
Remember the following while solving:
(i) Leave your logic aside about how things work helps.
(ii) While you can make common sense assumptions but do not bring in your own assumptions about things that may not be true always.
(iii) The assumption in the questions is something that the author believes.
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