Expert Systems and Languages for Artificial Intelligence (FSI-VES)

Academic year 2019/2020
Supervisor: RNDr. Jiří Dvořák, CSc.  
Supervising institute: ÚAI all courses guaranted by this institute
Teaching language: Czech
Aims of the course unit:
The goal is for students to understand the principles of working expert systems, be familiar with the languages of artificial intelligence and be able using them to create expert systems.
Learning outcomes and competences:
Knowledge of basic principles of working and building expert systems. Knowledge of functional, logic and rule-based programming. Ability to select and apply a suitable tool for expert system creation.
Prerequisites:
Mathematical principles of computer science, mathematical logic and probability theory.
Course contents:
The course begins with a description of the principles of expert systems. It continues with the introduction to selected languages for artificial intelligence (Lisp, Clips and Prolog) and their use for solving problems of artificial intelligence including the creation of expert systems. In the final part of the course, selected expert systems are presented and methods of uncertainty processing are described.
Teaching methods and criteria:
The course is taught through exercises focused to practical using the artificial intelligence languages (Lisp, Clips and Prolog) and to building expert systems.
Assesment methods and criteria linked to learning outcomes:
Requirements for graded course-unit credit: active participation in seminars, completion of final test and elaboration of semester project.
Controlled participation in lessons:
Attendance at the seminars is required. An absence can be compensated for via solving given problems.
Type of course unit:
    Computer-assisted exercise  13 × 2 hrs. compulsory                  
Course curriculum:
    Computer-assisted exercise 1. Introduction to expert systems.
2. Introduction to Lisp language.
3. Solving problems in Lisp, application examples.
4. Building expert systems in Lisp.
5. Introduction to Clips language.
6. Solving problems in Clips, application examples.
7. Building expert systems in Clips.
8. Introduction to Prolog language.
9. Solving problems in Prolog, application examples.
10. Building expert systems in Prolog.
11. Examples of commercial and non-commercial expert systems.
12. Handling uncertainty in expert systems.
13. Evaluating of semester projects.
Literature - fundamental:
1. Giarratano, J., Riley, G. Expert Systems. Principles and Programming. Boston, PWS Publishing Company 1998.
2. Jackson, P. Introduction to Expert Systems. Harlow, Addison-Wesley 1999.
3. Luger, G.F. Artificial Intelligence. Structures and Strategies for Complex Problem Solving. Harlow, Addison-Wesley 2008.
4. Bratko, I. Prolog Programming for Artificial Intelligence. Pearson Education 2011.
5. Luger, G.F.; Stubblefield, W.A. AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java. Addison-Wesley 2008.
Literature - recommended:
1. Mařík, V. a kol. Umělá inteligence. Praha, Academia.
2. Seibel, P. Practical Common Lisp. Apress, 2005. http://www.gigamonkeys.com/book/
3. Kelemen J. a kol. Tvorba expertních systémů v prostředí CLIPS. Praha, Grada 1999.
4. Merrit, D. Building Expert Systems in Prolog. Berlin, Springer-Verlag 1989. http://www.amzi.com/ExpertSystemsInProlog/index.htm
The study programmes with the given course:
Programme Study form Branch Spec. Final classification   Course-unit credits     Obligation     Level     Year     Semester  
M2I-P full-time study M-AIŘ Applied Computer Science and Control -- GCr 3 Compulsory-optional 2 1 S
M2I-P full-time study M-AIŘ Applied Computer Science and Control P linked to branch B-AIR GCr 3 Compulsory-optional 2 1 S