Using Decision Trees To Teach Value Of Information Concepts | Zendy

C. Jablonowski | Zendy

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Using Decision Trees To Teach Value Of Information Concepts

Author(s) -

C. Jablonowski

Publication year - 2020

Language(s) - English

Resource type - Conference proceedings

DOI - 10.18260/1-2--3141

Subject(s) - decision analysis , computer science , decision tree , influence diagram , decision engineering , value of information , variety (cybernetics) , business decision mapping , management science , value (mathematics) , set (abstract data type) , evidential reasoning approach , curriculum , decision support system , probabilistic logic , data science , artificial intelligence , machine learning , engineering , mathematics , programming language , psychology , pedagogy , statistics

Most undergraduate engineering economics textbooks and related curricula include elements of decision analysis, and decision trees are often introduced and promoted as a decision making tool. The teaching of value of information analysis is less prevalent, notwithstanding the variety of potential applications to everyday decisions in engineering practice. This paper addresses this gap by providing a detailed demonstration of how decision trees can be used to value information. It includes a detailed set of decision trees that guide the student through a decision under uncertainty. After definition of a base case, cases are provided for the value of perfect and imperfect information. The value of incremental improvement in information is addressed, and a probabilistic approach is described and demonstrated. The influence of risk preference is also addressed.

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