Artificial intelligence is the science that studies and develops methods of making computers more /intelligent/. The focus of this course is on core AI techniques for knowledge representation, search, reasoning, learning and designing intelligent agents. The course also aims to give an overview of other topics within AI, such as for example robotics, and of the historical, philosophical, and logical foundations of AI.

After completing this course, students should be able to:

1. Identify problems that are amenable to solution by AI methods, and which AI methods may be suited to solving a given problem.
2. Formalise a given problem in the language/framework of different AI methods (e.g., as a search problem, as a logical theory, as a planning problem, as an MDP, etc).
3. Implement basic AI algorithms (e.g., standard search algorithms or resolution).
4. Design and carry out an empirical evaluation of different algorithms on a problem formalisation, and state the conclusions that the evaluation supports.

Assignments (50%); Final Exam (50%)

Thirty one-hour lectures, six tutorials and six laboratory sessions.

COMP2100 or COMP2500; and COMP2600.

Stuart Russell and Peter Norvig (2010) Artificial Intelligence. A Modern Approach (3rd edition).

http://cs.anu.edu.au/student/comp3620/