Artificial Intelligence – Advanced Topics


Educational goals

The main purpose of the course is to introduce the problem solving techniques used in Artiicial Intelligence (AI), such as the methods of knowledge representation, reasoning and decision making. The course also aims to study the fields of applications and research of AI as well as current problem-solving techniques used in AI, such as, for example, intelligent agents, natural language processing, and digital assistants. In addition, the course aims to analyze the role of AI in the context of the 4th Industrial Revolution and to discuss the present and future effects of AI on work, economy and the society in general. Upon completion of the course students will be able to:

  • Know and apply techniques of Artificial Intelligence (AI), such as knowledge representation and reasoning, searching for solutions, natural language processing, and intelligent agents.
  • Analyse and evaluate current systems and applications of Artificial Intelligencee
  • Identify problems that can be solved using AI techniques
  • Study and constructively critique AI scientific and policy texts
  • Assess the role of modern and future applications of Artificial Intelligence in scientific and social development.
General Skills
  • Search, analyze and synthesize data and information, using the necessary technologies
  • Independent work
  • Teamwork
  • Demonstrate social, professional and ethical responsibility and sensitivity to the use of modern computer technology

Course Contents

The Field of Artificial Intelligence (AI): The weak and general View of AI
Knowledge Representation and Reasoning
State Space Problems and Solution Search Algorithms
Constrain Based Problem Solving Techniques
Intelligent Agents
Natural Language Processing
Digital Assistants
The impact of AI on work and its moral and social implications
National and European policies on AI

Teaching Methods - Evaluation

Teaching Method
  • Face to face theoretical teaching (lectures, discussion, problem solving and practice exercises).
  • Collaborative learning by studing state of the art AI issues/ working in teams
Use of ICT means
  • Using slide show presentation software.
  • Using an online learning platform (moodle).
  • Use of AI programming languages and specialised tools
Teaching Organization
Activity Semester workload
Study, writing and presentation of individual work30
Study, writing and presentation of teamwork40
Individual study and analysis of literature58
Total 180
Students evaluation

Assignements individual work presentation (20% of the rating)
Teamwork assignements presentation (40% of the rating)
Final Written Examination (40% of the rating) that includes:
- Short Answer Questions
- Multiple choice tests
- Problem solving

Recommended Bibliography

Recommended Bibliography through "Eudoxus"
  1. (Ελληνικά) Τεχνητή Νοημοσύνη – Θεωρητική Προσέγγιση της Επίλυσης Προβλημάτων με τη βοήθεια Μεθόδων Τεχνητής Νοημοσύνης. Κατερίνα Γεωργούλη. Ηλεκτρονικό Βιβλίο, Ανοικτά Ακαδημαϊκά Συγγράμματα (κεφάλαια: Εισαγωγή,1,2,3,6,7)
  2. Επιχειρηματική Ευφυΐα & Εξόρυξη Δεδομένων. Ευστάθιος Κύρκος. Ηλεκτρονικό Βιβλίο, Ανοικτά Ακαδημαϊκά Συγγράμματα (κεφάλαιο 1)
Complementary greek bibliography
  1. (Ελληνικά) Τεχνικές Λογικού Προγραμματισμού – Η Γλώσσα Prolog. Η. Σακελλαρίου, Π. Κεφαλάς, Ν. Βασιλειάδης, Δ. Σταμάτης, Έκδοση Ελληνικά Ακαδημαϊκά Ηλεκτρονικά Συγγράμματα
  2. Τεχνητή Νοημοσύνη. Ι. Βλαχάβας, Π. Κεφαλάς, Ν. Βασιλειάδης, Φ. Κόκκορας, Η. Σακελλαρίου. Εκδόσεις Πανεπιστημίου Μακεδονίας (4η έκδοση), 2020.
  3. Τεχνητή Νοημοσύνη - Μια Σύγχρονη Προσέγγιση, 2η έκδοση, S. Russel και P. Norvig, Κλειδάριθμος 2004. (Ελληνική μετάφραση Ι. Ρεφανίδης)
Complementary international bibliography
  1. S. Russell and P. Norvig Artificial Intelligence: A Modern Approach (2nd edition), Prentice Hall, 2nd ed., 2003