Augmenting a neural agent with an Oracle
Name
1078688378-MIT.pdf
Description
Full printable version
Size
326.94 KB
Format
Adobe PDF
Checksum (MD5)
8658a3f8e13bc1cec749f714da2251f8
Author(s)
Miranda, Zachery A
Advisor(s)
Armando Solar-Lezama.
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, I approached deep reinforcement learning agents with the novel idea of augmenting the agent with another neural network called an "Oracle" to gain more insights about the game environment. The Oracle is trained through supervised learning and can be used in various ways with the agent such as a reward shaper or in a pipeline with the agent through which it can transform the original input state into a more enhanced input state with more information. Overall results were not positive as creating a good Oracle can be hard. Creating a better Oracle could possibly display promising results.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 31-32).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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