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„POLITEHNICA” UNIVERSITY OF TIMIŞOARA
SYLLABUS
for the discipline:
“ADVANCED ARTIFICIAL INTELLIGENCE”
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER ENGINEERING
Year of studies: II (MASTER)
Semester: 1
Course instructor: professor Marius Crişan, PhD
Applications instructor: professor Marius Crişan, PhD
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
Project
2
0
2
0
Evaluation
E
Credits
9
A. COURSE OBJECTIVES
The course starts with a review of the theory and practice of the most advanced strategies in AI and how to
utilize the various techniques in knowledge-based systems. Then, the cognitive processes (perception, memory,
language and thought) are investigated. Finally, the main research approaches are presented that may lead to
valid intelligent techniques suitable for various applications. Upon completion of this course students will be
able to provide solutions for solving real human-like problems and develop their own research approaches.
B. COURSE SUBJECTS
1. Computational approaches in mental function modeling.
2. Models of vision and aural perception.
4
3. Memory systems.
4
4. Natural language processing
4
5. Reasoning and thinking models. 4
6. Learning and development.
4
7. Quantum model of brain.
4
Total 28
C. APPLICATIONS SUBJECTS
4
(laboratory, seminar, project)
1. Sensory system modeling based on self-organizing neural networks. 4
2. Models of perception and memory.
4
3. Complexity and information content analysis of cognitive systems. 4
4. Models of natural language understanding.
4
5. Approaches in Q & A systems. 4
6. Learning by simulating evolution.
4
7. Development of a mind/brain model based on quantum computing. 4
Total 28
D. REFERENCES
1. S. Russell and P. Norvig. “Artificial Intelligence- A Modern Approach.” Prentice Hall, 2003.
2. T. Malim: “Cognitive Processes”, Macmillan Press Ltd, 1994 (translated Ro. Ed. Tehnica 1999)
3. Speech and Language Processing: An Introduction to Natural Language Processing, Computational
Linguistics, and Speech Recognition. By Daniel Jurafsky and James H. Martin. Prentice-Hall,
2000.
E. EVALUATION PROCEDURE
There will be a final examination from lecture notes weighting 60% of the final grade. The lab assignments
weight 40% of the final grade.
F. INTERNATIONAL COMPATIBILITY Se pastreaza indicatiile din modelul in lb. romana
1. University of Houston: Advanced Artificial Intelligence
2. New York University: Advanced Artificial Intelligence
3. University of Adelaide: Advanced Artificial Intelligence
Date: 20.03.2008
HEAD OF DEPARTMENT
COURSE INSTRUCTOR,
Prof. Dr. ing. Vladimir CREŢU
Prof.dr.ing. Marius Crisan