Type of course: |
Compulsory |
Language of instruction: |
English |
Erasmus Language of instruction: |
English |
Name of lecturer: |
Maria Viorela Muntean |
Seminar tutor: |
Maria Viorela Muntean |
Form of education |
Full-time |
Form of instruction: |
Class |
Number of teaching hours per semester: |
42 |
Number of teaching hours per week: |
3 |
Semester: |
Autumn |
Form of receiving a credit for a course: |
Grade |
Number of ECTS credits allocated |
4 |
Course aims:
The course is a coherent introduction in Artificial Intelligence area, including theoretical and practical approaches.
The identification of appropriate models and methods for solving real-life problems.
The use of methodologies, specification mechanisms and development environments for the development of computer applications.
The use of computer and mathematical models and tools to solve specific problems in the application field.
Students will deal with the two AI approaches: symbolic and conexionist and they will use AI applications and languages.
Course Entry Requirements:
N/A
Course contents:
Introduction. Ai definitions. Short hystory of ai. Ai components
Problem solving. Solving problems by searching. Uninformed search strategies. Informed (heuristic) search strategies
Other problem solving strategies. Constraint satisfaction problems. Adversarial search (games)
Knowledge representation
Knowledge representation by rules
Structured knowledge
Uncertain knowledge and reasoning (fuzzy)
Planning and learning in AI systems
Artificial neural networks (ANN) foundations
ANNs applications
Expert Systems foundations
Intelligent agents and robots.
Teaching methods:
Lecture, conversation, exemplification.
Learning outcomes:
The use of methodologies, specification mechanisms and development environments for the development of computer applications.
The identification and explanation of base computer models that are suitable for the application domain.
The use of computer and mathematical models and tools to solve specific problems in the application field.
The identification of appropriate models and methods for solving real-life problems.
Learning outcomes verification and assessment criteria:
Written paper 50% Laboratory activities portfolio 50%
Recommended reading:
RUSSELL, Stuart J., NORVIG, Peter,
Artificial Intelligence: a modern approach, 3rd ed, Upper Saddle River, NJ: Pearson Education
, -
, 2010
, -
Van, HARMELEN Frank, LIFSCHITZ, Vladimir, PORTER, Bruce,
Handbook of knowledge representation, Oxford : Elsevier
, Amsterdam
, 2007
, -
WHITBY, Blay,
Artificial Intelligence: a beginner's guide, Oxford : Oneworld Publications
, -
, 2008
, -
-,
http://www.jessrules.com/jess/docs/71/index.html, -
, -
, -
, -
-,
http://www.expertise2go.com/, -
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