Introduction to Artificial Intelligence

Approved in the following curricular units:

– Programação;

– Programação Orientada a Objetos;

– Análise Matemática I e II.

The course consists of theoretical and practical lectures. Theoretical lectures present methodologies and examples of applications to case studies. The practical lectures focus on the implementation of algorithms and support the solution of practical work.

Students will be assessed on two components, theoretical (12 points) and practical (8 points).

The theoretical component is assessed by a written examination.

The practical component will be assessed by two practical assignments:

– Practical Assignment 1 – Rational Agents (2 marks);

– Practical Assignment 2 – Local Search and Evolutionary Computation (6 marks).

This unit explores the introductory concepts of Artificial Intelligence. The main objectives are:

– Acquire knowledge of the field of Artificial Intelligence;

– Provide an overview of the application of artificial intelligence techniques in real life;

– Know and apply problem solving techniques;

– Know and apply complex problem solving algorithms.

The competences to be acquired are

– Identify the main paradigms of artificial intelligence;

– Analyse an optimisation problem, identify its characteristics and isolate the basic components to be manipulated in its solution;

– Recognise the advantages and limitations of using problem solving algorithms;

– Justify the main choices made in the development of intelligent algorithms;

– Promote the autonomous development of new problem-solving strategies.

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

NAO

Main:

– S. Russell e P. Norvig, (2003). Artificial Intelligence: A Modern Approach. Prentice-Hall. (1A-4-125 (ISEC) – 11658).

Complementary:

Ertel, W. (2018). Introduction to artificial intelligence. Springer.

Michalewicz, Z., & Fogel, D. B. (2013). How to solve it: modern heuristics. Springer Science & Business Media.

Costa, E., & Simões, A. (2008). Inteligência artificial: fundamentos e aplicações, 2ª edição, FCA Editora de Informática.

Eiben, A. E., & Smith, J. E. (2003). Introduction to evolutionary computing (Vol. 53, p. 18). Berlin: springer.

Mitchell, T. M., & Learning, M. (1997). The McGraw-Hill Companies. Inc., New York.

Nilsson, N. J., & Nilsson, N. J. (1998). Artificial intelligence: a new synthesis. Morgan Kaufmann.