The effect of intermediate concepts in hierarchical relational learning

The DARPA Bootstrapped Learning project uses relational learners to ladder concepts together to teach a final concept, essentially narrowing the search space at each step. However, there are many ways to structure background knowledge to teach a concept and it is uncertain how different ways of structuring knowledge affects the accuracy and performance of learning. In this paper, we examine the effect of having intermediate concepts when learning high level concepts. We used Quinlan's First Order Inductive Learner to learn target selection for a real-time strategy game and did cross-validation tests with varying levels of intermediate concept support. The results show that including intermediate concepts does not always improve performance and accuracy.

Department dc:contributor.department

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

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2011

Author dc:creator

• Nga, Hout (Hout L.)

Advisor dc:contributor.advisor

• Howard Reubenstein and Leslie Pack Kaelbling.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about 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/1721.1/76993

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/76993