| Area of Mathematics: | Computational and Applied Mathematics (ECAM) | ||
| Semsster: | 7o | ||
| Course ID: | 72406 | ||
| Course Type: | Elective | ||
| Teaching hours per week: | Theory: 3 | Practice: 0 | Laboratory: 0 |
| ECTS : | 5 | ||
| Eclass: | |||
| Instructors: | |||
Description
Introduction to Artificial intelligence (AI), the history of AI. Problem formulation. Search Techniques (Uninformed and Informed). Knowledge representation (propositional logic and rules). Reasoning (predicate logic, fuzzy logic). Planning. Intelligent agents and distributed systems in AI. Non symbolic reasoning (genetic algorithms, neural networks). Applications (natural language processing, computer vision, robotics) and real world problem solving.
Bibliography
- Artificial Intelligence: A Modern Approach, 4th US ed., Stuart Russell and Peter Norvig ISBN-13: 978-0134610993
- Z. Michalewicz, D. Fogel. How to Solve It: Modern Heuristics. 2nd edition, Springer, 2004.
