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COMP20442: Artificial Intelligence Programming (2008-2009)

This is an archived syllabus from 2008-2009

Artificial Intelligence Programming
Level: 2
Credit rating: 10
Pre-requisites: No Pre-requisites
Co-requisites: No Co-requisites
Duration: 11 weeks in second semester
Lectures: 22 in total, 2 per week
Examples classes: None
Labs: 10 hours in total, 5 2-hour sessions.
Lecturers: Ian Pratt-Hartmann
Course lecturer: Ian Pratt-Hartmann

Additional staff: view all staff
Timetable
SemesterEventLocationDayTimeGroup
Sem 2 w19-26,30-33 Lecture LF15 Thu 11:00 - 12:00 -
Sem 2 w19-26,30-33 Lecture LF15 Tue 14:00 - 15:00 -
Sem 2 w21,23,25,30,32 Lab LAMB LambLab Thu 13:00 - 15:00 -
Assessment Breakdown
Exam: 80%
Coursework: 0%
Lab: 20%
Degrees for which this unit is optional
  • Artificial Intelligence BSc (Hons)

Aims

The aim of this course is to explain basic techniques of AI programming, with special focus on the Prolog programming language and its application to processing natural language.

Learning Outcomes

A student completing this course unit should:
Have a working knowledge of the Prolog programming language. (2)
Be able to write programs for computing the meanings of a range of natural language sentences. (3)
Understand the operation and use of automated theorem-provers, and the theoretical reasons for their limitations. (4)
Understand the fundamentals of natural language syntax. (5)
Understand how meaning-representations for natural language sentences can be computed.

Assessment of Learning outcomes

Learning outcomes (1), (2) and (3) are assessed by laboratory exercises. Learning outcomes (4) and (5) are assessed by examination and laboratory exercises.

Contribution to Programme Learning Outcomes

Course unit learning outcome (1) contributes to programme learning outcomes C5 and D2. Course unit learning outcome (2) contributes to programme learning outcomes B1, C5 , D2 and D6. Course unit learning outcome (3) contributes to programme learning outcomes A1 and A5. Course unit learning outcome (4) contributes to programme learning outcome A5. Course unit learning outcome (5) contributes to programme learning outcome A1 and A5.

Syllabus

Lectures 1--3


Basic Prolog programming

Lectures 4--6


The basic syntax of natural language: phrase-structure rules, agreement and movement.

Lectures 7--9


Incomplete data structures, grammar rules, more advanced techniques in natural language processing.

Lectures 10--13


Review of first-order logic: syntax and semantics. The lambda-calculus: basic techniques.

Lectures 14--17


Montague semantics: computing the meaning of natural language sentences.

Lectures 18--21


More first-order logic: proof and decidability. Theorem-proving techniques: correctness, completeness and termination.

Lecture 22


Grand finale: building a natural language reasoning program.

Reading List

Core Text
Title: Representation and inference for natural language: a first course in computational semantics
Author: Blackburn, Patrick and Johan Bos
ISBN: 1575864967
Publisher: CSLI (Center for the Study of Language and Information)
Edition:
Year: 2005


Core Text
Title: Learn Prolog now!
Author: Blackburn, Patrick and Johan Bos and Kristina Striegnitz
ISBN: 1904987176
Publisher: College Publications (Texts in Computing 7)
Edition:
Year: 2006