STUDENT is an early
artificial intelligence program that solves algebra word problems. It is written in
Lisp
A lisp is a speech impairment in which a person misarticulates sibilants (, , , , , , , ). These misarticulations often result in unclear speech.
Types
* A frontal lisp occurs when the tongue is placed anterior to the target. Interdental lisping ...
by
Daniel G. Bobrow as his PhD thesis in 1964 (Bobrow 1964). It was designed to read and solve the kind of word problems found in high school algebra books.
The program is often cited as an early accomplishment of AI in
natural language processing
Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to pro ...
.
Technical description
In the 1960s, mainframe computers were only available within a research context at the university. Within
Project MAC at
MIT, the STUDENT system was an early example of a
question answering
Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP), which is concerned with building systems that automatically answer questions posed by humans in a natural l ...
software which uniquely involved natural language processing and
symbolic programming. Other early attempts for solving
algebra story problems were realized with 1960s hardware and software as well: for example, the Philips, Baseball and Synthex systems.
STUDENT accepts an algebra story written in the English language as input, and generates a number as output. This is realized with a layered pipeline which consists of
heuristics for pattern transformation. At first, sentences in English are converted into kernel sentences, which each contain a single piece of information. Next, the kernel sentences are converted into mathematical expressions. The knowledge base which supports the transformation contains 52 facts.
STUDENT uses a
rule-based system with logic inference. The rules are pre-programmed by the software developer and are able to
parse natural language.
More powerful techniques for natural language processing, such as
machine learning, came into use later as hardware grew more capable, and gained popularity over simpler rule-based systems.
Example
(extracted from Norvig
)
References
Natural Language Input for a Computer Problem Solving System Bobrow's PhD thesis.
* , p. 19
* , pp. 76–79
History of artificial intelligence
{{compu-prog-stub