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Course content

The Master Artificial Intelligence is a one-year master course that leads to the title Master of Science (MSc). The course is rather intensive and requires sufficient knowledge to be acquired. Since the course is one year only, the requirements are rather severe, but the guidance is strict. In particular the system of project-centered education is an asset. Artificial intelligence (AI) focuses on the development of systems that perform tasks generally acknowledged to require intelligence. In its weak form, AI (i.e., “weak AI”) succeeded in enhancing the capabilities of computers by creating programs that can reason (e.g., chess programs, planning software), learn from examples (e.g., image-recognition programs, data-mining applications), or operate autonomously (e.g., single or multiagent systems). Strong AI claims that ultimately computers can be made to think both at and beyond the level of human beings. This form of AI has not been successful yet because the notions of thinking and reasoning are still poorly understood. Fundamental AI research focuses on issues such as the analogons of thinking and vision in situated agents, i.e., simple robots or autonomous agents operating in a realistic environment. Taken together, the weak and strong forms of AI face the challenge to develop smarter, more flexible, and more efficient computational devices ranging from desktop and laptop PC’s to portable wireless handhelds, PDA’s, and embedded devices.

The Master programme Artificial Intelligence covers a range of subjects emphasizing the following eight research topics:
(1) intelligent techniques for solving board games (e.g., chess and Go),
(2) intelligent techniques for controlling virtual characters (Game AI) in commercial computer games,
(3) agent technology for coordinating and controlling single and multiple agents,
(4) formal techniques for knowledge representation and reasoning in agents,
(5) machine learning to learn from examples in various domains
(6) situated agents to study the nature of low-level thinking processes,
(7) knowledge management to facilitate the exchange and distribution of knowledge among human and artificial agents,
(8) techniques and methods for knowledge retrieval.

The members of the teaching staff are actively involved in one or more of the eight research topics. As a result, the educational contents of the courses relate directly to the research performed.




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