Description

Theory
2

Laboratory
2

Instructors

Constantino Martins

Contents

P1. Logic Programming
P1.1. Brief introduction
P1.2. Basic concepts
P1.3. Recursiveness and lists.
P1.4. Multiple solutions and memory manipulation.
P1.5. Applications in Prolog for Artificial Intelligence.
P2. Functional Programming (Python)
P2.1. Lambda Calculation
P2.2. Knowledge Representation and Interrogation
P2.3. Lists
P2.4. Knowledge Representation Structures
P2.5. Functional Programming in Python
P3. Programming with Constraints
P3.1. Satisfaction of Constraints
P3.2. Finite Domain Constraint Programming
P3.3. Constraint Programming in Continuous Domains and Constraints on Sets
P4. Multi Paradigm Programming, Complementary Paradigms
P5. Introduction to various approaches to Artificial Intelligence
P5.1. Introduction to the Symbolic Approach
P5.2. Introduction to the Statistical / Probabilistic Approach
P5.3. Introduction to the Connectionist Approach
P5.4. Introduction to the Evolutionary Approach

Learning Outcomes

C01 ? Identify the main programming paradigms used in Artificial Intelligence.
C02 ? Apply paradigms such as logic, functional, and constraint programming to problem solving.
C03 ? Analyse and integrate different AI approaches, assessing the suitability of each paradigm to the given problem.
C04 ? Design and implement computational solutions for real-world problems of medium complexity, using the studied paradigms.
C05 - Develop transversal skills related to teamwork in response to challenges (AI Challenges4Teams).