Artificial intelligence

NA

About 60% of the lessons comprise oral presentation and discussion.

For one or more classes, external professors or researchers may be invited to speak about their research or other topics of the syllabus.

The remainder lessons are used for a practical component, where the students must choose one or more topics of their interest and study them in more detail, as well as implement one or more intelligent agents.

Globally the students must spend about 40 hours doing research and implementation for the practical component.

The student must get an insight into the principles behind intelligence, intelligent agents and the most common architectures. Students must develop the skills necessary to plan and implement intelligent agents able to solve common problems, using the techniques studied.

Natural, artificial and computational intelligence.

The origins and historic debates of Artificial Intelligence.

Characteristics of environments and common agent architectures. Learning agents.

Introduction to neural networks.

Genetic algorithms and adaptive agents.

Natural language processing. Applications to robotics.

• - For the final evaluation, reports of the practical component and presentations contribute 10 points, while a written test contributes the remainder. It is mandatory to achieve at least 40 % in each component. - 100.0%

NAO

“Artificial Intelligence – A modern Approach”, Stuart Russel and Peter Norvig, Prentice Hall.

“Inteligência Artificial – Fundamentos e Aplicações”, Ernesto Costa e Anabela Simões, FCA.