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Semester | fall semester 2017 |
Course frequency | Every fall sem. |
Lecturers |
Malte Helmert (malte.helmert@unibas.ch, Assessor)
Gabriele Röger (gabriele.roeger@unibas.ch) |
Content | 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. |
Learning 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. |
Bibliography | 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. |
Weblink | course web page |
Admission requirements | 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. |
Course application | Course: https://services.unibas.ch/ Exercises: https://courses.cs.unibas.ch/ |
Language of instruction | English |
Use of digital media | Online, mandatory |
Course auditors welcome |
Interval | Weekday | Time | Room |
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No dates available. Please contact the lecturer.
Modules |
Electives Master Computer Science: Recommendations (Master Computer Science (Start of studies before 01.08.2016)) Modul Concepts of Machine Intelligence (Master's degree subject: Computer Science) Modul Praxis aktueller Informatikmethoden (Master's degree subject: Computer Science (Start of studies before 01.08.2016)) Module Applications of Distributed Systems (Master Computer Science) Module Computer Sciences: Core Area (Master Computer Science (Start of studies before 01.08.2016)) Module Computer Sciences: Core Area (Master's degree subject: Computer Science (Start of studies before 01.08.2016)) Module Concepts of Machine Intelligence (Master Computer Science) |
Assessment format | continuous assessment |
Assessment details | 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. |
Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
Repeat examination | no repeat examination |
Scale | 1-6 0,5 |
Repeated registration | as often as necessary |
Responsible faculty | Faculty of Science, studiendekanat-philnat@unibas.ch |
Offered by | Fachbereich Informatik |