Course Information

Course Name	Turkish	Robotlarda Zeka
	English	Robot Intelligence
Course Code	BLG 622E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Sanem Sarıel Uzer
Course Objectives		1.To introduce the advanced techniques within artificial intelligence (AI), with particular focus on automated planning, uncertainty modeling and multiagent/multirobot systems, 2.To give an ability to carry out advanced research within artificial intelligence, 3.To give an ability to apply the knowledge learned on intelligent robot system design and development, 4.To provide the principles and methodologies to contribute to the AI field by developing novel solutions.
Course Description		The course covers the following subjects: knowledge representation and reasoning for logical agents and robots, reasoning under uncertainty, automated planning for autonomous robots, conditional/continual planning, scheduling and optimization, integrated planning and scheduling, probabilistic reasoning for robots, probabilistic graphical models, Markov Decision Processes, Partially Observable Markov Decision Processes, reinforcement learning, multiagent/multirobot systems, resource allocation, distributed artificial intelligence algorithms. These subjects are investigated in the context of intelligent robotic systems.
Course Outcomes		Students who have met the objectives of the course will be able to: 1.Select appropriate techniques for a given AI problem for agents or robots, 2.Compare and assess the appropriateness of various techniques for solving a given AI problem, 3.Combine different AI techniques in a theoretically sound way and apply in a practically useful way on robots, 4.Independently explore the literature relevant to a specific AI project, 5.Contribute to extend an existing AI technique, present a new formulation to an unsolved problem or develop a more efficient technique to solve an AI problem, 6.Write a paper in the style of a conference article documenting the developed system, its contribution to the field and its underlying theories.
Pre-requisite(s)		BLG521E or an equivalent course is preferred.
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