Next to a common basis, you specialize in one of three tracks:

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 track 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.
Cognitive Processing
The cognitive processing track focuses on how AI techniques can help to understand human behavior and cognition. Specifically, you learn how human behavior can be captured in computer simulations (cognitive models) and how the predictions of these simulations can be tested in experiments. In the track you gain theoretical knowledge about and hands-on experience with modeling and experimentation.
The ability to reason is one of the primary forms of intelligence. Since language and reasoning are closely intertwined, the study of language is an important component in the study of reasoning. Conversely, we cannot understand language without understanding reasoning. This track addresses the question what correct reasoning is, how people can rationally reason with incomplete and uncertain information and resolve conflicts of opinion, and how reasoning and language interact. The student will learn an array of skills ranging from formal methods to conceptual analysis.