• Instructor: Stephan Schiffel (stephans+ru.is)
• Office: 3rd floor, Venus, 695-2998
• Theory Lectures: Tuesdays 13:10-14:45 (M123), Thursdays 9:20-10:05 (M109)
• Labs: Thursdays 13:10-14:45 (M106)
• Online Forum: http://ruclasses.proboards.com/index.cgi?board=arti2012 (You need to register using your own name)

Artificial Intelligence (AI) is devoted to the computational study of intelligent behaviour, including areas such as problem solving, knowledge representation, reasoning, planning and scheduling, machine learning, perception and communication. This course gives an overview of the aforementioned AI subfields from a computer science perspective and introduces fundamental solution techniques for addressing them. An important part of the course is an independent final project where the students develop AI software in an area of their choice.

On the completion of the course the students should:

• have a good overview of the field of artificial intelligence (AI) and a thorough understanding of the fundamental solution methods used to attack a wide variety of AI-related problems.
• have gained experience building a small special-purpose AI system.

The textbook for this class is: “Artificial Intelligence: A Modern Approach” by Stuart Russell and Peter Norvig. This book has a very good web site full of useful AI resources.

You hand in the (almost) weekly assignments. These will mainly consist of small exercises in which you have to apply what you should have learned in the lecture. The questions should give you an indication of the questions that may be asked in the final exam.

You complete two programming assignments. This can be done as a group project (up to 3 people). Make sure you clearly indicate who is part of the group and that every group member clearly understands the solution.

The first programming assignment is to use search to find a good solution for a vacuum cleaning robot.

The second programming assignment is to program a connect-4 agent.

You can choose a topic for the final programming project (discuss topics and find a group in the forum). Like the programming assignments, this can be done as a group project (up to 3 people). You have to hand in a 1-2 page description of the project goal and some ideas on how to achieve it in week 8 (10% of the final grade) and demonstrate the final project in week 12 (20% of the final grade).

Project topics:

• Andrea Monacchi “An Early Warning System for Ambient Assisted Living” (part of a master thesis)
• Axel Gauti Guðmundsson, Heiðar Þórðarson “Dr. Dragon: Starcraft bot extraordinaire”
• Bæring Gunnar Steinþórsson, Viktor Þorgeirsson “Chat bot”
• Baldur Már Helgason, Jökull Jóhannsson “Path following robot”
• Guðmundur Siemsen Sigurðarson, Ingi Steinn Guðmundsson “Starcraft: Attack or Flee”
• Oddur Aðalgeirsson, Rúnar Freyr Rúnarsson “Starcraft: Ranged vs. Melee Unit”
• Ólafur Unason “Assassin Robot in Robocode”

Pathfinding Search (lab material) | | |

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