Introduction to Expert Systems (MAE846): Διαφορά μεταξύ των αναθεωρήσεων
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(Νέα σελίδα με '=== General === {| class="wikitable" |- ! School | School of Science |- ! Academic Unit | Department of Mathematics |- ! Level of Studies | Undergraduate |- ! Course Code | MAE846 |- ! Semester | 8 |- ! Course Title | Introduction to Expert Systems |- ! Independent Teaching Activities | Lectures (Weekly Teaching Hours: 3, Credits: 6) |- ! Course Type | Special Background |- ! Prerequisite Courses | - Logic Programming, Data Structure |- ! Language of Instruction...') |
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! Prerequisite Courses | ! Prerequisite Courses | ||
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Logic Programming, Data Structure | Logic Programming, Data Structure | ||
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=== Learning Outcomes === | === Learning Outcomes === | ||
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Αναθεώρηση της 20:58, 29 Ιουνίου 2022
General
| School |
School of Science |
|---|---|
| Academic Unit |
Department of Mathematics |
| Level of Studies |
Undergraduate |
| Course Code |
MAE846 |
| Semester |
8 |
| Course Title |
Introduction to Expert Systems |
| Independent Teaching Activities |
Lectures (Weekly Teaching Hours: 3, Credits: 6) |
| Course Type |
Special Background |
| Prerequisite Courses |
Logic Programming, Data Structure |
| Language of Instruction and Examinations |
Greek |
| Is the Course Offered to Erasmus Students |
Yes (in English) |
| Course Website (URL) | - |
Learning Outcomes
| Learning outcomes |
The goal of this course is the deeper understanding of PROLOG. During the course a detailed examination of the following topics are done:
After completing the course the student can handle: • theoretical documentation of problems • solving exercises • implementations-applications |
|---|---|
| General Competences |
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Syllabus
- Ιntroduction to Expert Systems
- Main Features of Expert Systems, classic examples
- Knowledge acquisition and verification, knowledge representation, inference and interpretation, consistency and uncertainties.
- Inference techniques
- Rule-based forward chaining Expert Systems
- Rule-based backward chaining Expert Systems
- Rule-based Expert Systems
- Expert Systems tools
- Users Interface
- Machine learning, decision making machines, Expert Systems examples.
Teaching and Learning Methods - Evaluation
| Delivery |
Face to face | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Use of Information and Communications Technology | Yes , Use of Natural Language and Mathematical Problems Processing Laboratory | ||||||||||
| Teaching Methods |
| ||||||||||
| Student Performance Evaluation |
Final test |
Attached Bibliography
- Γεώργιος Ι. Δουκίδης, Μάριος Κ. Αγγελίδης, "Έμπειρα συστήματα, τεχνητή νοημοσύνη και LISP", ISBN 960-08-0004-9, ISBN-13 978-960-08-0004-3
- Σπύρος Τζαφέστας, "ΕΜΠΕΙΡΑ ΣΥΣΤΗΜΑΤΑ ΚΑΙ ΕΦΑΡΜΟΓΕΣ", ISBN: - (Κωδικός Βιβλίου στον Εύδοξο: 89871)
- Παναγιωτόπουλος Ιωάννης - Χρήστος Π., "Νέες Μορφές Τεχνολογίας - Γενικευμένα Αυτόματα Συστήματα - Έμπειρα Συστήματα Turbo Prolog"