Overall objectives:

1 - The main objective of the discipline of Embedded Artificial Intelligence is to prepare students to use Artificial Intelligence as a work tool in support of development and research in different areas, with the possibility of exploring the different embeded platforms.

Syllabus:

1 - Introduction to Artificial Intelligence
2 - Problem-solving
3 - Knowledge, reasoning, and planning
4 - Uncertain knowledge and reasoning
5 - Machine Learning
6 - Communicating, perceiving, and acting
7 - Hardware Platforms for Embedded Implementations
8 - Hardware Implementation
9 - Artificial Intelligence Aplications

Literature/Sources:

Stuart Russell and Peter Norvig , 2020 , Artificial Intelligence: A Modern Approach, 4th edition , Pearson
Costa, E. e Simões, A. , 2008 , Inteligência Artificial, Fundamentos e Aplicações , FCA

Assesssment methods and criteria:

Classification Type: Quantitativa (0-20)

Evaluation Methodology:
The teaching of the contents, in the theoretical component, is for the presentation of the concepts, definitions and methodologies. The theoretical-practical component, with practical examples, aims to stimulate students to apply the studied methodologies that are concretized in the realization of project work. The evaluation is made with three project works relating to different parts of the studied material, with a total weight of 100%. None of these elements can have a weight greater than 50%.