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COMP24412: Symbolic AI (2010-2011)

This is an archived syllabus from 2010-2011

Symbolic AI
Level: 2
Credit rating: 10
Pre-requisites: COMP10412
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: Allan Ramsay
Course lecturer: Allan Ramsay

Additional staff: view all staff
Timetable
SemesterEventLocationDayTimeGroup
Sem 2 Lecture 1.3 Mon 14:00 - 15:00 -
Sem 2 Lecture 1.3 Tue 16:00 - 17:00 -
Sem 2 A w3+ Lab G23 Tue 11:00 - 13:00 G
Sem 2 A w3+ Lab UNIX Thu 11:00 - 13:00 I
Assessment Breakdown
Exam: 80%
Coursework: 0%
Lab: 20%

Themes to which this unit belongs
  • Natural Language, Representation and Reasoning

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.

Programme outcomeUnit learning outcomesAssessment
B1 C5 D2 D6Have a working knowledge of the Prolog programming language.
  • Lab assessment
A1 A5Be able to write programs for computing the meanings of a range of natural language sentences.
  • Lab assessment
A5Understand the operation and use of automated theorem-provers, and the theoretical reasons for their limitations.
  • Lab assessment
  • Examination
A1 A5Understand the fundamentals of natural language syntax.
  • Examination
  • Lab assessment
C5 D2Understand how meaning-representations for natural language sentences can be computed.
  • Lab assessment

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