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The course provides an introduction to concepts, models and algorithms for autonomous agents and multi-agent systems. The first part of the course introduces single-agent models and control architectures; the second, more extensive part explains key multiagent models and algorithms, both for cooperative and non-cooperative multiagent settings. Upon successful completion of the course, students will be able to understand main multi-agent concepts, be able to map real-world multi-agent problems to multiagent formal models and apply algorithmic techniques to solve them.
Both the course assessment and exam are required to pass the course. The final grade (A..F) will be determined by the sum of points obtained from the assessment and exam (<50 = F, 50-59 pts = E, …, 90-100 pts = A).
Minimum of 20 pts is required from three course miniprojects (out of maximum 40 pts)
The penalty for submitting the homework assignment after the deadline, but no later than 24 hours after the deadline, is 50% of the points. The penalty for submitting the homework assignment later than 24 hours after the deadline is 100% of the points.
Minimum of 30 pts is required from the exam (out of maximum 60 pts).
Exam from the last years: PDF
(subject to permutation)
(relevant chapters specified in respective lectures slides)