Total Credits: 10
Level: Level 2
Target Students: Part I undergraduate students in the School of Computer Science. Also available to students from other Schools with the agreement of the module convenor. Available to JYA/Erasmus students.
|Spring||Assessed by end of Spring Semester|
Prerequisites: or equivalent (eg G52AIM 2009/10)
|G52PAS||Planning and Search|
Summary of Content:
This module is part of the Intelligent Systems theme in the School of Computer Science.
This module introduces basic AI programming techniques and explains how these can be used to solve typical AI problems (e.g., those introduced in G51IAI and G52PAS). The programming techniques are introduced through an AI programming language, however the emphasis is on transferrable AI programming skills rather than language specific details. Topics covered include: introduction to Prolog, Horn clauses, unification, backtracking, lists and other data structures, and AI programming patterns. Key AI problems are used to illustrate practical exercises, e.g., basic search, planning, game playing, etc.
Method and Frequency of Class:
|Activity||Number Of Weeks||Number of sessions||Duration of a session|
|Lecture||11 weeks||2 per week||1 hour|
|Computing||11 weeks||1 per week||2 hours|
Method of Assessment:
|Exam 1||75||1hr written examination|
|Coursework 1||25||AI programming coursework|
Dr B Logan
Education Aims: To develop new analysis, design and programming skills appropriate to more complex AI problems.
Learning Outcomes: Knowledge and Understanding: Understanding of the theory and practice of AI programming and how AI programming techniques can be used to solve typical AI problems. Intellectual Skills: Enhanced program analysis and design skills. Professional Skills: The ability to write programs in Prolog. Transferable Skills: Problem solving.
Offering School: Computer Science
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