Lecture: Planning and Optimization

Course Number 45400-01
Lecturers Malte Helmert
Gabriele Röger
Assistants Florian Pommerening
Tutors Cedric Geissmann
Salome Eriksson
Time and Location Mon 14:15 - 16:00; Seminarraum 00.003, Spiegelgasse 1
Wed 14:15 - 16:00; Seminarraum 00.003, Spiegelgasse 1
Start 20-09-2017
Exercises Wed 16:15 - 18:00; Seminarraum 05.001, Spiegelgasse 5
Prerequisites Good knowledge in the foundations and core areas of computer science are assumed, in particular algorithms and data structures, complexity theory, mathematical logic and programming.

Good knowledge of the contents of the course "Foundations of Artificial Intelligence" (13548) is assumed, in particular the chapters on state-space search. Students who have not previously passed the prerequisite course are strongly advised to learn the necessary material in self-study prior to the beginning of this course. If you are interested in participating in this course but do not yet have strong knowledge on state-space search, we strongly encourage you to contact the lecturers prior to the semester to discuss a possible self-study plan.
Objectives The participants get to know the theoretical and algorithmic foundations of action planning as well as their practical implementation. They understand the fundamental concepts underlying modern planning algorithms as well as the theoretical relationships that connect them. They are equipped to understand research papers and conduct projects in this area.
Contents The course provides an introduction to the theory and algorithms for classical planning, with an emphasis on heuristic search methods. Classical planning is concerned with finding action sequences (plans) that transform a given initial state into a state satisfying a goal condition in very large state spaces. Topics covered include: planning formalisms and normal forms; progression and regression; computational complexity of planning; planning heuristics based on delete relaxation, abstraction, critical paths, landmarks and network flows; theoretical connections between planning heuristics and the concept of cost partitioning; symbolic search.
Literature There is no textbook for the course. The course slides will be made available to the participants, and additional research papers complementing the course materials will be uploaded to the course webpage during the semester.
Assessment Lehrveranst.-begleitend

Please note: Oral examination
Dates: Monday, 5 February; Tuesday, 6 February; Wednesday, 7 February
Room: Office 06.004
Marked homework exercises will be handed out weekly in order to assess the learning progress. To qualify for the oral examination, students must obtain at least 50% of the total marks from the exercises. Exercise marks do not contribute to the final grade for the course, which is exclusively based on the oral examination.
Credit Points 8
Grades 1-6 0,5
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Modul Concepts of Machine Intelligence (MSF - Computer Science)
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