Introduction to Artificial Intelligence

Base Knowledge

Approval in the curricular units of:

– Programação;

– Programação Orientada a Objetos;

– Análise Matemática I e II.

Teaching Methodologies

The course includes theoretical and practical lectures. The theoretical lectures present the methodologies and examples of applications to case studies. Practical classes focus on the implementation of algorithms and give support to the resolution of practical works. Students are evaluated based on two components, Theoretical (12 points) and Practical (8 points). The theoretical component is assessed through a written examination. The evaluation of the practical component is performed through two practical works:
Pratical Assignment 1 – Rational Agents (2 points)
Pratical Assignment 2 – Local Search and Evolutionary computation (6 points)

Learning Results

By the end of this course, students should be able to:
–   Identify the main paradigms and algorithms of Artificial Intelligence
–   Analyze an optimization problem, identify its main characteristics, basic components and apply the correct algorithms
–   Recognize the advantages and limitations of the different algorithms for problem solving
–   Justify the main options taken during the developments of the algorithms
–   Develop in an autonomous way new strategies for problem solving

Program

1.   Artificial Intelligence – A General Overview
2.   Rational Agents and Problem Solving
3.   Search Methods
3.1   Non-Informed Search
3.2   Heuristic Search
4.   Local Search Techniques
5.   Evolutionary Computation
6.   AI in Games
7.   Machine Learning

Curricular Unit Teachers

Internship(s)

NAO