Introdução à Inteligência Artificial

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Lectures and discussion of themes are given about 60% of the semester. For one or two of the classes, external speakers are invited to speak on some particular topics. The remaining classes are allocated for students to investigate and develop one or more intelligent agents on topics of choice within the UC program.

The student must understand the notions of intelligent agent and the main architectures. It must be able to conceive, design and implement an autonomous intelligent agent capable of solving common problems, using the learned techniques.

Notions of natural and artificial intelligence.

The origins of AI and historical debates.

Characterization of environments and agents.

Learning paradigms.

Neural networks.

Genetic algorithms and adaptive agents.

Troubleshooting by search.

Natural language processing.

• - The evaluation is based on lecture reports (1 point per lecture), a written test (8-9 points) and one or more practical assignments that are worth the rest. - 100.0%

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