Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 1 of 1
Full-Text Articles in Entire DC Network
Toward Self-Reconfigurable Parametric Systems: Reinforcement Learning Approach, Ting-Yu Mu
Toward Self-Reconfigurable Parametric Systems: Reinforcement Learning Approach, Ting-Yu Mu
Dissertations
For the ongoing advancement of the fields of Information Technology (IT) and Computer Science, machine learning-based approaches are utilized in different ways in order to solve the problems that belong to the Nondeterministic Polynomial time (NP)-hard complexity class or to approximate the problems if there is no known efficient way to find a solution. Problems that determine the proper set of reconfigurable parameters of parametric systems to obtain the near optimal performance are typically classified as NP-hard problems with no efficient mathematical models to obtain the best solutions. This body of work aims to advance the knowledge of machine learning …