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
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