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COMP24412: Symbolic AI (2012-2013)

This is an archived syllabus from 2012-2013

Symbolic AI
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.
Course Leader: Ian Pratt-Hartmann
Additional Lecturers: Allan Ramsay
Course leader: Ian Pratt-Hartmann

Additional staff: view all staff
Timetable
SemesterEventLocationDayTimeGroup
Sem 2 Lecture 1.5 Mon 14:00 - 15:00 -
Sem 2 Lecture 1.5 Tue 16:00 - 17:00 -
Sem 2 A w3+ Lab LF31 Thu 11:00 - 13:00 I
Sem 2 A w3+ Lab LF31 Tue 11:00 - 13:00 G
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.
  • Examination
  • Lab assessment
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

The following list specified the order in which material will be covered; however, it is not a timetable. Lectures may take more than one session if required. There is a block of time at the end of the course for catching up and revision.

Lectures 1--3


Basic Prolog programming

Lecture 4


Search techniques in AI

Lectures 5--6


Logic

Lectures 7--8


Theorem-Proving

Lectures 9-13


Natural language syntax.

Lectures 14 - 17


Natural language semantics.

Lectures 18--22


Catch-up and revision.

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