Course Information

Course Name	Turkish	Mekatronik Mühendisliğinde Özel Konular
	English	Special Topics in Mechatr.Eng.
Course Code	MKM 511E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Ali Fuat Ergenç
Course Objectives		Reinforcement Learning (RL) is a powerful paradigm where an agent learns to take sequential decisions in a complex environment in order to accomplish a goal. RL has been applied successfully in a myriad of problems in various fields such as robotics, games, finance and healthcare. In the maritime domain, applications cover autonomous vessels, collision avoidance, navigation and maritime traffic management. This course will provide a solid foundation to the participants in the field of reinforcement learning. During the introduction to RL, the course will cover main concepts such as Markov Decision Processes, value functions and optimality. The course will then touch upon Dynamic Programming, but mainly focus on sample-based learning methods with function approximations. The use of deep learning techniques in RL (deep RL) will be the central topic of the course. The course project will be about heading keeping of ships in waves in numerical simulations using deep RL
Course Description		Reinforcement Learning (RL) is a powerful paradigm where an agent learns to take sequential decisions in a complex environment in order to accomplish a goal. RL has been applied successfully in a myriad of problems in various fields such as robotics, games, finance and healthcare. In the maritime domain, applications cover autonomous vessels, collision avoidance, navigation and maritime traffic management. This course will provide a solid foundation to the participants in the field of reinforcement learning. During the introduction to RL, the course will cover main concepts such as Markov Decision Processes, value functions and optimality. The course will then touch upon Dynamic Programming, but mainly focus on sample-based learning methods with function approximations. The use of deep learning techniques in RL (deep RL) will be the central topic of the course. The course project will be about heading keeping of ships in waves in numerical simulations using deep RL
Course Outcomes
Pre-requisite(s)		Basic Probability, Statistics and Machine Learning, and proficiency in Python.
Required Facilities
Other
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