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

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thesis
posted on 20.12.2021, 15:51 by Aishwarya Vikram DeshpandeAishwarya Vikram Deshpande

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.

History

Degree Type

Master of Science

Department

Computer Science

Campus location

Indianapolis

Advisor/Supervisor/Committee Chair

Snehasis Mukhopadhyay

Additional Committee Member 2

Mihran Tuceryan

Additional Committee Member 3

Yuni Xia