Introduction to Artificial Intelligence

Recommended Prerequisites

Programming Skills: Introduction to Programming and Problem Solving, Principles of Procedural Programming. Mathematical Skills: Discrete Structures, Statistics, Theory of Information

Teaching Methods

This curricular unit includes theoretical lectures where the fundamental concepts, principles and techniques are presented and explained in detail. Their application to real world situations is also explored in order to promote the interest of the students.

Lectures of theoretical-practical nature play the role of strengthening the connection between theoretic knowledge and their practical application.

The laboratory classes focus on: (i) development of the projects (ii) solving exercises.

Learning Outcomes

This curricular unit aims at the acquisition of solid base knowledge on the field of artificial intelligence in terms of: foundations, techniques and practical application. To serve this purpose the integrating concept of Agent is adopted. The development of agents of increasing complexity and capabilities inspired in three different metaphors – symbolic, connectionist and biological – is studied. Considering the key role they play, particular relevance is given to the concepts of state, state change operator, and state space.

 

The main competencies to be developed are:

Instrumental – analysis and synthesis, problem solving

Personal – critical thinking

Systemic - practical application of the theoretical knowledge; research

 

The secondary competences are:

Instrumental – organizing and planning

Personal – work in teams

Systemic – autonomous learning; creativity

Work Placement(s)

No

Syllabus

1. Introduction
   1. Defining Artificial Intelligence
   2. Agents
   3. Environments
   4. Tasks
   5. State, state change operator, and state space
2. Agents with fixed structure
   1. Reactive
   2. Search
3. Agents with variable structure
   1. Larning
   2. Adaptive
4. Society of Agents
5. Representation, Knowledge, Uncertainty, Reasoning

 

The following topics will be addressed for each type of agent:

1. Arquitecture
2. Representation and Reasoning
3. Implementation according to each of the following metaphors: symbolic, connectionism, biologica
4. Aplication to problems

Head Lecturer(s)

Fernando Jorge Penousal Martins Machado

Assessment Methods

Assessment
Two projects: 40.0%
Exam: 60.0%

Bibliography

Costa, E., Simões, A.: Inteligência Artificial - Fundamentos e Aplicações, FCA - Editora de Informática, 2008.

Russell, S., Norvig, P.: Artificial Intelligence - A Modern Approach. Pearson Education 2010: I-XVIII, 1-1132