Learning Outcomes
Cognitive:
Understanding the basic theory for simple and sequential decisions by an intelligent agent, familiarization with the types of decision support systems, understanding the theory of decision making with data analysis, understanding the basic principles of game theory, understanding computational issues in developing decision support systems, familiarization with the use of decision support software.
Skills:
Training on developing decision support systems, training on the use of decision support tools.
Course Content (Syllabus)
Introduction, Decision Making under Certainty (Multi-criteria Decision Making Methods), Decision Making under Ignorance, Decision Making under Risk (Probability Theory, Bayesian Networks, Utility Theory), Sequential Decisions (Decision Trees), Decision Making in the presence of Competitive Agents (Game Theory), Decision Making with Data Analysis (Machine Learning, Knowledge Discovery in Databases, Business Intelligence.
Course Bibliography (Eudoxus)
i) Τεχνητή Νοημοσύνη: Μια σύγχρονη προσέγγιση, S Russel, P. Norvig, ΚΛΕΙΔΑΡΙΘΜΟΣ, ISBN: 9602098732,
ii)Τεχνητή Νοημοσύνη, Ι. Βλαχάβας, Π. Κεφαλάς, Ν. Βασιλειάδης, Φ. Κόκκορας, Η. Σακελλαρίου, Γ' Έκδοση, Εκδόσεις Πανεπιστημίου Μακεδονίας, 2011, ISBN: 978-960-8396-64-7