This paper gives an overview of artificial intelligence, including intelligent search, logic-based and probabilistic knowledge representation and reasoning, and machine learning.
Students will get a broad overview of AI research and applications, and will be able to apply AI ideas and implement algorithms for selected problems, especially in search, knowledge representation and reasoning, as well as in machine learning.
COMP203 Programming with Data Structures or
COMP241 Software Engineering Development
Official Timetable Information
This is just a rough guideline, but on average we would expect you to spend 9 hours on reading, thinking, and doing your assignments in addition to lecture time. That's about 12 hours a week.
Russell, S. and Norvig, P., Artificial Intelligence: A Modern Approach, (3rd edition).
The Linux computers in Lab 6 in R block.
Internal assessment/final examination ratio 2:1 or 1:2, whichever works in your favour.
An overall mark of 50% is required for a pass, with a minimum of 35% in the final exam.
see Moodle page
The textbook and the lecture slides will probably enable you to follow the course. However, there will be additional explanations in class, as well as interaction that you might find useful.
We will closely follow the book
- Stuart Russell, Peter Norvig, "Artificial Intelligence: A Modern Approach (2nd edition)", Prentice Hall, 2010.
The plan is to cover the following topics:
- Solving Problems by Searching
- Informed Search and Exploration
- Adversarial Search
- Knowledge Representation & Reasoning
- Probabilistic Reasoning
- Making Simple Decisions
- Learning from Observations
- Knowledge in Learning
- Neural Networks
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