| Course Unit Code | 155-0346/02 |
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| Number of ECTS Credits Allocated | 5 ECTS credits |
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| Type of Course Unit * | Compulsory |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | Second Year |
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| Semester when the Course Unit is delivered | Winter Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| ROZ01 | Ing. Petr Rozehnal, Ph.D. |
| Summary |
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| The aim of the course is to acquire basic knowledge and skills in selected areas of artificial intelligence and expert systems and their application in selected areas of economics, particularly game theory, decision making under conditions of uncertainty, application of expert systems and others. |
| Learning Outcomes of the Course Unit |
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1. To gain a basic knowledge of the state space and the methods of its searching
2. To understand the principle of the resolution method
3. To understand the principles of the Horn clauses and their relation on the program development in the Prolog programming language
4. To gain a knowledge of the expert systems, their properties and components
5. To understand the expert system inference mechanism
6. Be able to apply the expert systems in the chosen areas of economics in practice
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| Course Contents |
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1. History of science Artificial intelligence and its applications
2. State space and its basic properties
3. State space search methods and their comparison
4. Fundamentals of first-order predicate calculus
5. Resolution method and Horn clauses
6. Logic programming and Prolog programming language
7. Expert systems, their features and components
8. Methods of knowledge representation in expert systems
9. Processing uncertain information in the development of expert systems
10. The inference mechanism of expert systems
11. Machine learning and expert systems
12. Application of expert systems in selected economic areas |
| Recommended or Required Reading |
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| Required Reading: |
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LUGER, George F. Artifical Intelligence: Structures and Strategies for Complex Problem Solving. Sixth Edition. Boston: Addison Wesley, 2009. 743 s. ISBN 978-0-321-54589-3.
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| MAŘÍK, Vladimír, Olga ŠTĚPÁNKOVÁ, Jiří LAŽANSKÝ et al. Umělá inteligence 1. Praha: Academia, 1993. 264 s. ISBN 80-200-0496-3. |
| Recommended Reading: |
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| GIARRATANO, Joseph C. a Gary D. RILEY. Expert Systems: Principles and Programming. Fourth Edition. 2004. 831 s. ISBN 978-0534384470. |
| BRATKO, Ivan. Prolog Programming for Artificial Intelligence. Fourth Edition. London:Pearson Education. 2011. 696 s. ISBN 978-0321417466. |
| Planned learning activities and teaching methods |
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| Lectures, Tutorials |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Exercises evaluation and Examination | Credit and Examination | 100 (100) | 51 |
| Exercises evaluation | Credit | 45 | 20 |
| Examination | Examination | 55 | 6 |