2026-09-19T01:29:38Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1131482026-06-06T00:48:53Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Tomaso Poggio.
Hege, Phillip Gabriel
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2018-01-12T20:59:48Z
2018-01-12T20:59:48Z
2017
2017
http://hdl.handle.net/1721.1/113148
1018306715
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
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 (page 41).
In this thesis, I designed and implemented a framework for reinforcement learning (RL) agents to interact with a web environment. With this framework, I introduce a new challenge for RL agents to learn human activity on the web. By defining a series of tasks such as using the web as a navigable resource to perform actions, I introduce an extension to natural language processing models. The framework provides an agent with rich features including element positioning, color, and size in order to process text represented in a 2D web space..
by Phillip Gabriel Hege.
M.Eng.
41 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Developing a generalized intelligent agent by processing information on webpages
Thesis
application/pdf
false
Publication
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="18590530-5081-4e11-b1a6-b2cfe3d77f45">
<Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type>
<Language>eng</Language>
<Title>Developing a generalized intelligent agent by processing information on webpages</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>2017</PublicationDate>
<Authors>
<Author>
<DisplayName>Hege, Phillip Gabriel</DisplayName>
<Affiliation>
<OrgUnit>
</OrgUnit>
</Affiliation>
</Author>
</Authors>
<Editors>
</Editors>
<Publishers>
<Publisher>
<DisplayName>Massachusetts Institute of Technology</DisplayName>
<OrgUnit />
</Publisher>
</Publishers>
<License>http://dspace.mit.edu/handle/1721.1/7582</License>
<Keyword>Electrical Engineering and Computer Science.</Keyword>
<Abstract>In this thesis, I designed and implemented a framework for reinforcement learning (RL) agents to interact with a web environment. With this framework, I introduce a new challenge for RL agents to learn human activity on the web. By defining a series of tasks such as using the web as a navigable resource to perform actions, I introduce an extension to natural language processing models. The framework provides an agent with rich features including element positioning, color, and size in order to process text represented in a 2D web space..</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>