| Course Unit Code | 460-4093/01 |
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| Number of ECTS Credits Allocated | 4 ECTS credits |
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| Type of Course Unit * | Choice-compulsory |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | First Year |
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| Semester when the Course Unit is delivered | Summer 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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| MEN059 | Mgr. Marek Menšík, Ph.D. |
| Summary |
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| The course will provide the fundamentals of logic programming. Students will learn how to specify a program in the declarative way as a knowledge base of facts and rules. We will also deal with evaluation strategies based on resolution method and with the foundations of machine learning. |
| Learning Outcomes of the Course Unit |
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| The course will provide the fundamentals of logic programming. Students will learn how to specify a program in the declarative way as a knowledge base of facts and rules. We will also deal with evaluation strategies based on resolution method and with the foundations of machine learning. |
| Course Contents |
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Lectures:
1. The structure of a logical program
2. Communication with Prolog interpreter, quering
3. Prolog evaluatiuon strategies.
4. Syntactic structures of Prolog (facts, rules, lists, built-in predicates,…)
5. Simple applications; relational databases, graphs, natural language processing
6. Recursion
7. Cut vs. not
8. Crisp vs. fuzzy approach (theory and practice)
9. Introduction to fuzzy Prolog (Ciao Prolog), Aggregation operators, syntax
10. Applications of fuzzy logic programming
11. Artificial intelligence in agent systems; machine learning algorithms in Prolog.
12. Graphic interface in LPA Prolog
Seminars:
1. The structure of a logical program
2. Communication with Prolog interpreter, quering
3. Prolog evaluatiuon strategies.
4. Syntactic structures of Prolog (facts, rules, lists, built-in predicates,…)
5. Simple applications; relational databases, graphs, natural language processing
6. Recursion
7. Cut vs. not
8. Crisp vs. fuzzy approach (theory and practice)
9. Introduction to fuzzy Prolog (Ciao Prolog), Aggregation operators, syntax
10. Applications of fuzzy logic programming
11. Artificial intelligence in agent systems; machine learning algorithms in Prolog.
12. Graphic interface in LPA Prolog
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| Recommended or Required Reading |
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| Required Reading: |
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[1] J. W. Lloyd. Foundations of Logic Programming (2nd edition). Springer-Verlag 1987.
[2] I. Bratko. PROLOG. Programming for Artificial Intelligence (3rd edition). Addison Wesley 2001.
[3] W.F. Clocksin, C.S. Mellish. Programming in Prolog. Springer-Verlag 1987.
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[1] J. W. Lloyd. Foundations of Logic Programming (2nd edition). Springer-Verlag 1987.
[2] I. Bratko. PROLOG. Programming for Artificial Intelligence (3rd edition). Addison Wesley 2001.
[3] W.F. Clocksin, C.S. Mellish. Programming in Prolog. Springer-Verlag 1987.
[4] M. Bieliková, P. Návrat. Funkcionálne a logické programovanie. STU Bratislava 2000.
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| Recommended Reading: |
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| [1] D. DeGroot, G. Lindstrom. Logic Programming; Functions, Relations and Equations. Prentice Hall, New Jersey, 1986. |
| [1] D. DeGroot, G. Lindstrom. Logic Programming; Functions, Relations and Equations. Prentice Hall, New Jersey, 1986. |
| Planned learning activities and teaching methods |
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| Lectures, Individual consultations, Tutorials, Project work |
| 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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| Graded credit | Graded credit | 100 | 51 |