COMP24412: Symbolic AI (2010-2011)
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 outcome||Unit learning outcomes||Assessment|
|B1 C5 D2 D6||Have a working knowledge of the Prolog programming language.|
|A1 A5||Be able to write programs for computing the meanings of a range of natural language sentences.|
|A5||Understand the operation and use of automated theorem-provers, and the theoretical reasons for their limitations.|
|A1 A5||Understand the fundamentals of natural language syntax.|
|C5 D2||Understand how meaning-representations for natural language sentences can be computed.|
Basic Prolog programming
The basic syntax of natural language: phrase-structure rules, agreement and movement.
Incomplete data structures, grammar rules, more advanced techniques in natural language processing.
Review of first-order logic: syntax and semantics. The lambda-calculus: basic techniques.
Montague semantics: computing the meaning of natural language sentences.
More first-order logic: proof and decidability. Theorem-proving techniques: correctness, completeness and termination.
Grand finale: building a natural language reasoning program.
Core TextTitle: Representation and inference for natural language: a first course in computational semantics
Author: Blackburn, Patrick and Johan Bos
Publisher: CSLI (Center for the Study of Language and Information)
Core TextTitle: Learn Prolog now!
Author: Blackburn, Patrick and Johan Bos and Kristina Striegnitz
Publisher: College Publications (Texts in Computing 7)