Control prin invatare 2019 / Learning control 2019

Lecturer: Lucian Busoniu

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About this course

This course provides methods for controlling systems that are too complex or insufficiently known to apply classical control design techniques. The focus is placed on learning algorithms for control, in particular reinforcement learning (RL). Special attention is also paid to model-based techniques related to RL, as they can be very useful in controlling complex systems even when a model is known. After introducing the RL problem, the dynamic programming algorithms that sit at the foundation of RL are described in the discrete-variable context. Then, classical RL algorithms are introduced in the same context. In the second part of the course, the dynamical programming and RL algorithms are extended with approximation techniques, in order to make them applicable to continuous-variable control, as well as to large-scale discrete-variable problems. Finally, several online planning techniques are discussed.

This course is part of the Master program ICAF of the Automation Department, UTCluj (1st year 2nd semester). As prerequisites, basic knowledge of analysis and linear algebra is needed, together with notions of discrete-time dynamical systems. The lecturer is Lucian Busoniu.

The course and lab sessions take place on Thursdays from 18:00, in room C01, Dorobantilor. A detailed schedule is given next. Due to scheduling constraints two weeks are free.

Week; day Session
#1; 28 Feb Lecture 1
#2; 7 Mar Lecture 2
#3; 14 Mar Lab 1
#4; 21 Mar Lecture 3
#5; 28 Mar Free
#6; 4 Apr Lecture 4
#7; 11 Apr Lab 2
#8; 18 Apr Lecture 5
#9; 25 Apr Lecture 6
#10; 9 May Lab 3
#11; 16 May Lecture 7
#12; 23 May Lecture 8
#13; 30 May Lab 4
#14; 6 Jun Free

Grading rules:

You can check your current status in the online status table (updated in real-time).

Lectures

The slides are made available here in time for each lecture. The slides are required material for the exam. They, as well as the lectures, are in Romanian.

At the end of each lecture, a quiz will be given from the material discussed in that lecture. At the end of the semester, each student obtains a number of points in the grade, equal to the number of questions answered correctly divided by the total number of questions asked during the semester.

Labs

In the lab classes, a set of assignments must be solved. A solution consists of a brief report in PDF and associated Matlab code, and must be submitted by a specified deadline. For each lab, the full code or a specified part of it should be completed during the lab session itself. In addition, an oral session with mandatory participation will be organized before the exam (the exact date will be announced later), where the lecturer will discuss the solutions separately with each student group. In this session, detailed questions will be asked to clearly assess whether the assignment solution is original, and the contribution of each student to this solution.

Submitting the solutions to all the assignments, as well as validating these solutions by discussing them in the oral session, is required before being admitted to the exam. There is zero tolerance for copying; each copied solution is graded 0, and having two or more copied solutions automatically invalidates the entire solution set and the student must redo the discipline in the following year. More details on the requirements (including individual deadlines) are available in the assignment descriptions, which will appear here shortly before the corresponding lab session.

In addition, 2 points of each lab grade are awarded as a result of a short (5 minutes) test in the beginning of the class, which covers lecture material relevant to that lab.

Contact

Comments, suggestions, questions etc. related to this course or website are welcome; please contact the lecturer.