Computer Laboratory > Teaching > Course material 2007–08 > Computer Science Tripos Syllabus and Booklist 2007-2008 > Artificial Intelligence I

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Artificial Intelligence I

Lecturer: Dr S.B. Holden

No. of lectures: 12

Prerequisite courses: Algorithms I + II (CST students) or Data Structures and Algorithms (Part II (General)/Diploma students). In addition the course requires some mathematics, in particular some use of vectors and some calculus. For Part II (General) and Diploma students therefore Mathematics for Computation Theory is desirable. For CST students Part IA Natural Sciences Mathematics or equivalent, and Discrete Mathematics I + II, are likely to be helpful although not essential.

This course is a prerequisite for Artificial Intelligence II (Part II).

Aims

The aim of this course is to provide an introduction to some basic issues and algorithms in artificial intelligence (AI). The course approaches AI from an algorithmic, computer science-centric perspective; relatively little reference is made to the complementary perspectives developed within psychology, neuroscience or elsewhere. The course aims to provide some basic tools and algorithms required to produce AI systems able to exhibit limited human-like abilities, particularly in the form of problem solving by search, representing and reasoning with knowledge, planning, and learning.

Lectures

Objectives

At the end of the course students should

Recommended reading

* Russell, S. & Norvig, P. (2003). Artificial intelligence: a modern approach. Prentice Hall (2nd ed.).
Cawsey, A. (1998). The essence of artificial intelligence. Prentice Hall.
Luger, G.F. & Stubblefield, W.A. (1998). Artificial intelligence: structures and strategies for complex problem solving. Addison-Wesley.
Dean, T., Allen, J. & Aloimonos, Y. (1995). Artificial intelligence: theory and practice. Benjamin/Cummings.



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