Knowledge Based Systems
We will investigate both the scientific aim of AI - insight into human mental activity such as "intelligence, thinking & creativity" – and the technical aim: to create programs that solve problems requiring "intelligent, heuristic & subjective" judgements. One can divide AI by topic – decision support systems, natural language, vision or robotics – or by type: knowledge representation, diagnosing, supervision, planning, knowledge acquisition, learning & pattern recognition. Not only will traditional AI approaches be covered but also more modern KBS approaches will be introduced: Mobile Agents, Neural Nets, Genetic algorithms, Artificial Life and Virtual Reality.
This course is the natural start of studies within the area "Artificial Intelligence, Robotics, Evolutionary Computation & Neural Nets", which is described in more detail in
http://www.daimi.au.dk/~brian/ai.html.
This course can not be part of the final exam.
Lecturer:
Brian Mayoh
Literature:
Nils J. Nilsson "Artificial Intelligence: a new synthesis", Kauffman 1998, ISBN 1-55860-535-5 (paper) & articles
Prerequisites:
dArkOS, dDistSik and dADS
Assignments:
Important compulsory assignment (half of the time of the course)
Evaluation:
Approval of the compulsory assignment
Lectures:
2 hours/week
Course Language:
Danish or English
Credits:
10 ECTS
Quarter
3+4