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Multi-criteria decision making using reinforcement learning and its application to food, energy, and water systems (FEWS) problem

Indiana University-Purdue University Indianapolis (IUPUI) / Multi-criteria decision making (MCDM) methods have evolved over the past several decades. In today’s world with rapidly growing industries, MCDM has proven to be significant in many application areas. In this study, a decision-making model is devised using reinforcement learning to carry out multi-criteria optimization problems. Learning automata algorithm is used to identify an optimal solution in the presence of single and multiple environments (criteria) using pareto optimality. The application of this model is also discussed, where the model provides an optimal solution to the food, energy, and water systems (FEWS) problem.

Identiferoai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/27395
Date12 1900
CreatorsDeshpande, Aishwarya
ContributorsMukhopadhyay, Snehasis, Tuceryan, Mihran, Xia, Yuni
Source SetsIndiana University-Purdue University Indianapolis
Languageen_US
Detected LanguageEnglish
TypeThesis
RightsCC0 1.0 Universal, http://creativecommons.org/publicdomain/zero/1.0/

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