Maestría en Ciencias Computacionales

Knowledge Representation
Summer 2014

Professor: Dr. Rogelio Dávila Pérez

E-mail: rdav90@gmail.com

General objective of the course:

At the end of the course the student will be able to:

Know basic models and techniques in which Logic Programming is supported.
Identify real situations where these technologies may be applyied with success.
Apply the technologies to real problems where conventional techniques do not provide adecuate solutions.
Value the application limits for the corresponding techniques.

PROJECTS

EVALUATION

First Partial Examination (25%)
First exam 90%
Activities and Homeworks 10%,
Total 100%

Second Partial Examination (35%)
Second exam 90%
Activities and Homeworks 10%,
Total 100%

Final Examination (40%)
Final exam 90%
Activities and Homeworks 10%,
Total 100%

TOTAL EVALUATION
2 partial examinations: 25% + 35% = 60%
Final examinationl: 40%,
Total: 100%

TEXT BOOK

	Knowledge Representation, Reasoning, and the Design of Intelligent Agents The Answer-Set Programming Approach by Michael Gelfond and Yulia Kahl Cambridge University Press (2014)

CONSULTING MATERIAL

Knowledge Representation, Reasoning
and Declarative Problem Solving
Chitta Baral
Cambridge University Press (2003)

SOFTWARE DE APOYO

Aspide, DLV para Windows o Mac.