Description

Theory
2

Laboratory
2

Instructors

Luiz Faria

Contents

1- Knowledge Representation (11 hours; 15%)
Knowledge classification and knowledge representation techniques
2- Ontologies (4 hours; 5%)
Ontology representation languages, ontology engineering, and applications
3- Knowledge Based Systems (7 hours; 10%)
Features and examples of Knowledge Based Systems; Temporal Reasoning; Truth Maintenance
4 ? Expert Systems (34 hours; 45%)
Expert Systems architecture and components
5- Reasoning under Uncertainty (11 hours; 15%)
Bayesian/Probabilistic and Fuzzy Logic approaches
6- Semantic Web (4 hours; 5%)
Semantic Web (RDF ? Resource Description Framework) and Web Ontologies (OWL ? Web Ontology Language)
7- Knowledge Management (4 hours; 5%)
Knowledge in organizations, Knowledge acquisition and discovery, Knowledge Externalization and Internalization, Knowledge sharing, Verification and Validation, Knowledge Maintenance

Learning Outcomes

CO1- Become aware, understand and apply the concepts related with Knowledge Based Systems, Ontologies and Semantic Web, and Knowledge Management (NB3)
CO2- Knowing and understanding a real problem that can be adequately treated using Knowledge Based Systems and Semantic Web, and analyzing, investigating, designing, implementing, experimenting, reviewing, testing, synthesizing and evaluating in order to solve this problem using the methods presented in the course (NB6)
CO3- To select and apply techniques able to deal with uncertain and incomplete information (NB3)
CO4- Develop transversal skills related to teamwork in response to challenges (AI Challenges4Teams) (NB6)