Developing a generalized intelligent agent by processing information on webpages

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..

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Hege, Phillip Gabriel

Advisor dc:contributor.advisor

• Tomaso Poggio.

• Electrical Engineering and Computer Science.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/113148

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/113148