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ASU Electronic Theses and Dissertations


This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.


Achieving human level intelligence is a long-term goal for many Artificial Intelligence (AI) researchers. Recent developments in combining deep learning and reinforcement learning helped us to move a step forward in achieving this goal. Reinforcement learning using a delayed reward mechanism is an approach to machine intelligence which studies decision making with control and how a decision making agent can learn to act optimally in an environment-unaware conditions. Q-learning is one of the model-free reinforcement directed learning strategies which uses temporal differences to estimate the performances of state-action pairs called Q values. A simple implementation of Q-learning algorithm can be …

Contributors
Gankidi, Pranay Reddy, Thangavelautham, Jekanthan, Ren, Fengbo, et al.
Created Date
2016

The information era has brought about many technological advancements in the past few decades, and that has led to an exponential increase in the creation of digital images and videos. Constantly, all digital images go through some image processing algorithm for various reasons like compression, transmission, storage, etc. There is data loss during this process which leaves us with a degraded image. Hence, to ensure minimal degradation of images, the requirement for quality assessment has become mandatory. Image Quality Assessment (IQA) has been researched and developed over the last several decades to predict the quality score in a manner that …

Contributors
Gunavelu Mohan, Aswin, Sohoni, Sohum, Ren, Fengbo, et al.
Created Date
2017