Competencies and objectives

 

Course context for academic year 2017-18

Automated Reasoning is a subject that provides an overview of actual techniques and discussions of artificial intelligence based on human reasoning. It ranges from the classic logics to the most modern Machine Learning, Learning Theory and the PAC model.

Despite having a particular agenda, Automated Reasoning is a subject open to all topics, allowing students to develop, know and practice them from a professional point of view, with real problems. The focus of the course is entirely practical, with hands on problems for students that will take their skills to the limit, improving and expanding them.

Posed problems will use simulation environments based in computer games and nowadays Artificial Intelligence contests. In general, the subject will follow a Project Based Learning approach.

 

 

Course content (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2017-18

Specific Competences (Specific Technology):>>Computer Science

  • CEC4 : Capacitat per a conèixer els fonaments, paradigmes i tècniques pròpies dels sistemes intel·ligents i analitzar, dissenyar i construir sistemes, serveis i aplicacions informàtiques que utilitzen aquestes tècniques en qualsevol àmbit d'aplicació.
  • CEC5 : Capacitat per a adquirir, obtenir, formalitzar i representar el coneixement humà en una forma computable per a la resolució de problemes mitjançant un sistema informàtic en qualsevol àmbit d'aplicació, particularment els relacionats amb aspectes de computació, percepció i actuació en ambients o entorns intel·ligents.
  • CEC7 : Capacitat per a conèixer i desenvolupar tècniques d'aprenentatge computacional i dissenyar i implementar aplicacions i sistemes que les utilitzen, incloent-hi les dedicades a l'extracció automàtica d'informació i coneixement a partir de grans volums de dades.

 

Basic Competences

  • CB3 : Que els estudiants tinguen la capacitat de reunir i interpretar dades rellevants (normalment dins de la seua àrea d'estudi) per a emetre judicis que incloguen una reflexió sobre temes rellevants d'índole social, científica o ètica

 

 

 

Learning outcomes (Training objectives)

No data

 

 

Specific objectives stated by the academic staff for academic year 2017-18

Course goals

  • Analyze AI from the point of view of Automated Reasoning.
  • Understand the importance of Automated Reasoning as an application in video games.
  • Learning how to properly design an Artificial Intelligence Engine.
  • Learn to design, implement and optimize an AI under low computational limitations.
  • Learn and implement basic techniques of Automated Reasoning like Finite State Machines, Decision Trees, Fuzzy Logic and Goal-Driven Reasoning.
  • Learn to improve Pathfinding and planning models to produce results of Automated Reasoning.
  • Know Machine Learning, the PAC model (Probably Approximately Correct), Learning Theory and Generalization.
  • Learn and implement some Machine Learning models like Linear and Logistics Regression, Neural Networks, Genetic Algorithms and Support Vector Machines.

 

 

General

Code: 34031
Lecturer responsible:
GALLEGO DURAN, FRANCISCO JOSE
Credits ECTS: 6,00
Theoretical credits: 0,60
Practical credits: 1,80
Distance-base hours: 3,60

Departments involved

  • Dept: SCIENCE OF COMPUTING AND ARTIFICIAL INTELLIGENCE
    Area: SCIENCE OF COMPUTING AND ARTIFICIAL INTELLIGENCE
    Theoretical credits: 0,6
    Practical credits: 1,8
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught