Curriculum

Choose four electives from the list below.

Logic and Language (TLMV13020)

An intelligent agent is an artificial (computer-based) entity that can act pro-actively, reactively, autonomously and rationally in a dynamic environment. Agents can reason about the situation they are in, plan their actions given their goals, revise their beliefs, learn from experience, adapt to the environment, communicate and cooperate. This area focuses on (1) the logical modelling, programming and application of intelligent agents and multi-agent systems; and (2) the use of probabilistic and sub-symbolic machine learning techniques for making agents learn, and adapt to their environment and to other agents. Area Representative: Brian Logan (b.logan@uu.nl)

The cognitive processing area focuses on how AI techniques can help to understand human behaviour and cognition. Specifically, you learn how human behaviour can be captured in computer simulations (cognitive models) and how the predictions of these simulations can be tested in experiments. You gain theoretical knowledge about and hands-on experience with modelling and experimentation. Area Representative: Martijn Mulder (m.j.mulder@uu.nl)

The ability to reason is one of the primary forms of intelligence. This area addresses the question what correct reasoning is, how people can rationally reason with incomplete and uncertain information and resolve conflicts of opinion, how to formalise reasoning as a logic, what the best representations of a logic are, and how reasoning and language interact. The student will learn an array of skills ranging from formal methods to conceptual analysis. Area Representative: Rosalie Iemhoff (r.iemhoff@uu.nl)

Natural language plays a central role in many sub-domains of AI. Obviously, we would want artificially intelligent systems to be able to perform certain kinds of linguistic behaviour: natural language comprehension, generation, translation etc. Additionally, there are vast amounts of linguistically represented data - think of the proportion of the internet that is text-based - and we would like to be able to use that data for AI tasks. In this area you learn about models of linguistic human behaviour and linguistic output, using symbolic, logical and probabilistic methods. You learn to explore the suitability of these models for natural language processing. Finally, you will also learn a range of experimental techniques to develop and test models. Area Representative: Lasha Abzianidze (l.abzianidze@uu.nl)

Students who finish the programme obtain two separate degrees, i.e. one diploma for each Master’s programme. By combining research projects the total study load is 180 EC. Usually, the double Master’s programme can be finished in three years or less. The Board of Examiners of both Master's programmes have to approve the proposed programme.

This programme is highly selective and only the very best students, with proven excellent academic records, are admitted. Typically, you need to be in the top 10% of your class and have completed your bachelor's degree without delay.

Information and application

To be admitted to this programme, please contact the programme coordinator of one of the two Master’s programmes involved. Your application will then be considered by the programme leaders of both Master’s programmes. You also need to be enrolled in both the participating Master’s programmes. For Dutch or EU/EER-students there is no additional tuition fee.

Together with the programme coordinators, you have to fill out and sign this Double Degree Master's Programme form and complete this with a motivation letter. You can upload this form together with your application in Osiris Case.

For more information, please consult the Education and Examinations Regulations or contact one the Master’s programme coordinators.