Knowledge Engineering is the process of building and maintaining intelligent problem-solving systems that use (symbolic) AI methods. This MSc level module provides covers selected methods from all areas of Knowledge Engineering. Topics include knowledge representation and reasoning, knowledge acquisition, knowledge synthesis and knowledge evolution.
The module descriptor can be found here.
The course follows the textbook "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig (2nd edition, Prentice-Hall, 2003).
For the lectures on agents and multiagent systems, recommended readings are "An Introduction to Multiagent Systems" by Michael Wooldridge (John Wiley & Sons, 2002) and "Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence" by Gerhard Weiss (MIT Press, 1999).
"A Semantic Web Primer" by Grigoris Antoniou and Frank van Harmelen (MIT Press, 2004) is a comprehensive textbook on Semantic Web technologies.
Generally speaking, you don't need to buy these books to follow the KE module. Where slides are not self-contained, I will provide additional material on this page. Also, the university library has several copies in stock (both in the reserve collection and in the standard collection). However, the book is a good long-term investment for those interested in AI.
A second source of material are the module notes by Alan Smaill and Qiang Shen from a previous Knowledge Engineering course (2003), they can be retrieved here.
Explicit reference to specific chapters of these two sources made on the lecture slides page. Lecture slides will be made available after the individual lecture sessions, however, I will attempt to post preliminary versions on the evening before the respective session where possible.
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