INTELLIGENT AUTONOMOUS SYSTEMS

Course Information
TitleΕΥΦΥΗ ΑΥΤΟΝΟΜΑ ΣΥΣΤΗΜΑΤΑ / INTELLIGENT AUTONOMOUS SYSTEMS
CodeNIS-08-01
FacultySciences
SchoolInformatics
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorGrigorios Tsoumakas
CommonNo
StatusActive
Course ID40002975

Programme of Study: Undergradute Studies - School of Informatics (2015-today)

Registered students: 2
OrientationAttendance TypeSemesterYearECTS
Information SystemsElected Compulsory Directional845
Digital MediaElective Courses845
Communication, Networks And Systems ArchitectureElective Courses845
Information And Communication Technologies In EducationElective Courses845
General Common DirectionElective Courses845

Class Information
Academic Year2015 – 2016
Class PeriodSpring
Faculty Instructors
Weekly Hours4
Class ID
600052423
Type of the Course
  • Scientific Area
Course Category
Specific Foundation / Core
Mode of Delivery
  • Face to face
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Basic knowledge on Artificial Intelligence, Good knowledge of procedural programming.
Learning Outcomes
Training on basic principles of intelligent autonomous systems. Learning the basic compo-nents of intelligent robots. Familiarization with learning, reasoning and planning techniques for autonomous systems. Obtaining the ability to develop software for intelligent autonomous systems.
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
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Θέματα και Προκλήσεις Αυτόνομων Συστημάτων. Ιστορικά Στοιχεία. Παραδείγματα. Αρχιτεκτονικές Ρομπότ. Βιολογική Θεμελίωση. Σχεδιασμός Ενεργειών: Ιεραρχικός Σχεδιασμός, Εύρεση Μονοπατιού, Κατάστρωση Κινήσεων. Ευφυείς Πράκτορες: Επικοινωνία, Αρχιτεκτονικές, Έλεγχος Συμπεριφοράς, Αναπαράσταση, Αρχιτεκτονικές Συστημάτων. Ευφυής Διασύνδεση με Περιβάλλον: Αισθητήρες και Εξαρτήματα δράσης. Μάθηση στα Ευφυή Αυτόνομα Συστήματα: Μάθηση με Επίβλεψη, Νευρωνικά Δίκτυα, Γενετικοί Αλγόριθμοι, Ενισχυτική Μάθηση, Μέθοδοι Monte Carlo, Μάθηση Χρονικών Διαφορών, Μάθηση Χάρτη και Προσδιορισμός Θέσης σε αυτόν.
Educational Material Types
  • Notes
  • Slide presentations
  • Book
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
Description
Slides in electronic format, software tools & videos.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures521.7
Laboratory Work401.3
Reading Assigment401.3
Project
Total1324.4
Student Assessment
Description
Written Exams weighting 100%. Bonus grades from projects. The evaluation criteria are mentioned in the course webpages.
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Exam with Short Answer Questions (Summative)
  • Written Exam with Extended Answer Questions (Summative)
  • Written Assignment (Summative)
Bibliography
Course Bibliography (Eudoxus)
Βασικές Αρχές Ρομποτικής, Maja Mataric, Κλειδάριθμος 2010 , ISBN: 960-461-354-5
Additional bibliography for study
Συμπληρωματικές σημειώσεις (διαφάνειες μαθήματος)
Last Update
13-09-2013