Course Information

Cycle / Level
Teaching PeriodWinter
CoordinatorNick Bassiliades
Course ID40002242

Class Information

Academic Year2011 – 2012
Class PeriodWinter
Faculty Instructors
Weekly Hours4
Class ID
Type of the Course
  • Scientific Area
  • Skills Development
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
General Prerequisites
Basic knowledge of Artificial Intelligence, Basic knowledge of programming with rules.
Learning Outcomes
Knowledge: Familiarization with Knowledge Representation and Reasoning principles, Familiarization with Knowledge Engineering and basic Knowledge Systems development techniques, Training on CLIPS production system. Skills: Training on developing knowledge systems, Programming with CLIPS production rule language..
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
Course Content (Syllabus)
Knowledge Representation (Rules, frames, objects). Architecture of Knowledge Systems. Knowledge Engineering. (Development cycle. Knowledge Acquisition. KADS methodology. Verification & Validation. Development Tools.) Advanced Reasoning Techniques. (Model-based reasoning. Qualitative reasoning. Cased-based reasoning.) Applications of Knowledge Systems. (Classification. Configuration. Diagnosis and Troubleshooting.) Case Studies. CLIPS production rule system. (Facts, Rules, Matching, production cycle, Functions, constraints in rule conditions, fact templates, conflict resolution strategies, Objects - COOL (Classes, inheritance, instances, using objects in rules, messages, message handlers, object management, queries on objects, object functions)). Programming and developing Knowledge Systems.
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Powerpoint slides, CLIPS programming language demonstration
Course Organization
ActivitiesWorkloadTotal hours of student effort for the semester. Includes lectures, labs, field etc.ECTSThe credit units (ECTS) of the respective teaching activity. Each unit correponds to X hours of student workload.IndividualFor the learning activity cooperation between students is not requisiteTeamworkFor the learning activity the students cooperate in teamsErasmusThe learning activity is available to students of exchange programmes
Student Assessment
Written exams (70%), Programming Projects (30%)
Student Assessment methods
  • Written Exam with Multiple Choice Questions (SummativeSummative assessment refers to the assessment of the learning and summarizes the development of learners at a particular time.)
  • Written Exam with Short Answer Questions (SummativeSummative assessment refers to the assessment of the learning and summarizes the development of learners at a particular time.)
  • Written Assignment (FormativeFormative assessment is a range of formal and informal assessment procedures employed by teachers during the learning process in order to modify teaching and learning activities to improve student attainment., SummativeSummative assessment refers to the assessment of the learning and summarizes the development of learners at a particular time.)
Course Bibliography (Eudoxus)
Ι. Βλαχάβας, Π. Κεφαλάς, Ν. Βασιλειάδης, Φ. Κόκκορας, Η. Σακελλαρίου. Τεχνητή Νοημοσύνη - Γ' Έκδοση, Εκδόσεις Πανεπιστημίου Μακεδονίας, ISBN: 978-960-8396-64-7, 2006/2011.
Additional bibliography for study
- Introduction to Expert Systems, Jackson P., 3rd edition, Addison Wesley, ISBN 0-201-87686-8 - Introduction to Knowledge Systems, Stefik M., Morgan Kaufmann, ISBN 1-55860-166-X - Joseph C. Giarratano and Gary D. Riley, “Expert Systems: Principles and Programming”, Fourth Edition, Course Technology, Boston, MA, 2004. - CLIPS User's Guide (
Last Update
Winter period 2011