Catalogue of Modules, University of Nottingham

G52HPA History and Philosophy of Artificial Intelligence
(Last Updated:07 April 2014)

Year  09/10

Total Credits: 10

Level: Level 2

Target Students:  Second year undergraduate students in the School of Computer Science.  Available to JYA/Erasmus students.

Taught Semesters:

SemesterAssessment
Autumn Assessed by end of Autumn Semester 

Prerequisites: 

MnemTitle
G51IAI Introduction to Artificial Intelligence 

Corequisites:  None.

Summary of Content:  This module aims to provide an understanding of the philosophical issues surrounding Artificial Intelligence and a historical perspective on those issues and AI itself. It explores in greater depth issues presented in G51IAI, including the Turing Test and Strong and Weak AI, as well as relevant issues from the Philosophy of Mind. Students will be expected to review and critique key developments in the history of AI to understand how they continue to influence the development of the field.

Method and Frequency of Class:

ActivityNumber Of WeeksNumber of sessionsDuration of a session
Lecture 11 weeks2 per week1 hour
Tutorial 11 weeks1 per week1 hour

Activities may take place every teaching week of the Semester or only in specified weeks. It is usually specified above if an activity only takes place in some weeks of a Semester

Method of Assessment: 

Assessment TypeWeightRequirements
Coursework 1 100 Report based on lecture material, directed reading and research 

Convenor: 
Professor T Pridmore
Dr N Alechina

Education Aims:  To provide an understanding of the philosophical issues surrounding the subject of Artificial Intelligence and a historical perspective on those issues and on the subject itself.

Learning Outcomes:  Knowledge and Understanding: The theory of programming. The theoretical underpinnings, tools and techniques of Artificial Intelligence. Intellectual Skills: Think independently while giving due weight to the arguments of others. Understand complex ideas and relate them to specific problems or questions. Analyse systematically and effectively substantial quantities of information. Professional Skills: Transferable Skills: Communicate effectively in writing and orally. Retrieve information from appropriate sources (e.g. learning resource centre, internet, etc).

Offering School:  Computer Science


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