Base Knowledge
Introducion to AI (agents)
Teaching Methodologies
Powerpoint slides and some demonstration vídeos, complemented with application exercices
Problem resolution
Small project implementation based on development tools
Learning Results
To know and understand the tools for developing expert systems, case based reasoning, uncertainty representation, neural and Bayesian networks. To implement systems based on these models.
Capacity for using the tools above described within a short time period. Capacity for identifying problems that can be solved with these kind of systems in real situations. Knowledge acquisition. Understanding the application of expert systems, case based reasoning, fuzzy systems, probability based systems, neural and Bayesian networks.
Program
Neural Networks
Introduction to ESs
Case Based Reasoning
Uncertainty / Certainty factors and MYCIN / Fuzzy Logic and Mamdani Inference
Bayesian Networks
Practical Classes: Problems about all the subjects
Labs: Practical works woth Matlab, Drools and GENIE
Final Practical evaluation work
Curricular Unit Teachers
Internship(s)
NAO