Next to a common basis in AI, you choose courses from four areas:
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.
The cognitive processing area 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. 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. This area 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.
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