Learning from natural instructions

In this work we take a first step towards Learning from Natural Instructions (LNI), a framework for communicating human knowledge to computer systems using natural language. In this framework the process of learning is synonymous with language interpretation, the process in which natural language sentences are converted into a logical representation which can be understood by an automated agent. While the motivation behind this framework is clear, the practical aspects involved in constructing it are non-trivial: communicating effectively with computer systems has been one of motivating forces behind artificial intelligence research since its inception. The rigid way in which computer systems naturally take instructions, via programming, and the flexible and ambiguous way in which humans naturally provide instructions, via natural language, rendered this task extremely difficult.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2013

Author dc:creator

• Goldwasser, Dan

Contributors dc:contributor

• Roth, Dan
• DeJong, Gerald F.
• Hockenmaier, Julia C.
• Mooney, Raymond

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• Semantic Interpretation

Statement dc:rights

• Copyright 2012 Dan Goldwasser

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/42235

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/42235