Introduction

This course delves into the core principles and methods of Artificial Intelligence (60 hours x 6 courses). The curriculum, taught by professors with significant research experience, covers advanced AI topics such as data and text mining, multi-agent systems, image processing, knowledge-based systems, and ontology integration.

  • Daniel Manrique, 174h
  • Asunción Gomez, 62h
  • M. Carmen Suarez, 40h
  • Roberto Valle, 36h
  • Miguel García, 48h

Unit 1: Introduction to Artificial Intelligence

Foundations and scope of AI taught by Daniel Manrique and Asunción Gomez.

Unit 2: Knowledge Representation

Taught by Asunción Gomez and M. Carmen Suarez.

  • Production systems
  • Knowledge graphs
  • Taxonomic and N-ary relationships

Unit 3: Search Techniques

Taught by Daniel Manrique, Roberto Valle and Miguel García.

  • Uninformed search
  • Informed search
  • Constraint satisfaction
  • Adversarial search
  • State space search

Unit 4: Approximate Reasoning Models

Taught by Daniel Manrique and M. Carmen Suarez.

  • Reasoning under uncertainty
  • Fuzzy logic

Unit 5: Artificial Neural Networks

Taught by Daniel Manrique.

  • Introduction to Machine Learning
  • Neural network models
  • Backpropagation and learning