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45400-01 - Vorlesung: Planning and Optimization (8 KP)

Semester Herbstsemester 2026
Weitere Semesterveranstaltungen zu diesen KP 45400-01 (Vorlesung)
45400-02 (Übung)
Angebotsmuster Jedes Herbstsemester
Dozierende Malte Helmert (malte.helmert@unibas.ch, BeurteilerIn)
Gabriele Röger (gabriele.roeger@unibas.ch)
Inhalt The course provides an introduction to the theory and algorithms for automated planning, with an emphasis on classical planning. Automated planning is concerned with determining a sequence of actions that transforms a given initial state into a desirable state in a very large state space. Topics covered include: planning formalisms and normal forms; progression and regression; computational complexity of planning; heuristics for classical planning based on delete relaxation, abstraction, landmarks, critical paths and network flows; formal relationships between heuristics.
Lernziele 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.
Literatur 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

 

Teilnahmevoraussetzungen 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.

Most importantly, good knowledge of the contents of the courses "Theory of Computer Science" (10948) and "Foundations of Artificial Intelligence" (13548) is assumed, in particular the topic of NP-completeness from the theory course and the topics of state-space search and propositional logic from the AI course. Students who have not previously passed the prerequisite courses 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 sufficient knowledge of these topics, we strongly encourage you to contact the lecturers prior to the semester to discuss a possible self-study plan.
Anmeldung zur Lehrveranstaltung Registration via https://services.unibas.ch.
Unterrichtssprache Englisch
Einsatz digitaler Medien Online-Angebot obligatorisch
HörerInnen willkommen

 

Intervall Wochentag Zeit Raum
wöchentlich Montag 14.15-16.00 Spiegelgasse 1, Seminarraum 00.003
wöchentlich Mittwoch 14.15-16.00 Spiegelgasse 1, Seminarraum 00.003

Einzeltermine

Datum Zeit Raum
Montag 14.09.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 16.09.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 21.09.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 23.09.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 28.09.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 30.09.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 05.10.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 07.10.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 12.10.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 14.10.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 19.10.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 21.10.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 26.10.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 28.10.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 02.11.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 04.11.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 09.11.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 11.11.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 16.11.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 18.11.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 23.11.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 25.11.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 30.11.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 02.12.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 07.12.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 09.12.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Montag 14.12.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 16.12.2026 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Module Doktorat Informatik: Empfehlungen (Promotionsfach: Informatik)
Modul: Applications of Distributed Systems (Masterstudium: Computer Science (Studienbeginn vor 01.08.2026))
Modul: Concepts of Machine Intelligence (Masterstudium: Computer Science (Studienbeginn vor 01.08.2026))
Modul: Concepts of Machine Intelligence (Master Studienfach: Computer Science (Studienbeginn vor 01.08.2026))
Modul: Electives in Data Science (Masterstudium: Data Science)
Modul: Machine Intelligence (Masterstudium: Computer Science)
Modul: Machine Intelligence (Master Studienfach: Computer Science)
Modul: Methods of Machine Intelligence (Masterstudium: Computer Science (Studienbeginn vor 01.08.2026))
Prüfung Lehrveranst.-begleitend
Hinweise zur Prüfung Marked homework exercises will be handed out in order to support and assess the learning progress. To qualify for the written 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 written examination.
Expected date: Wednesday, January 27, 2027, 2-4 p.m.

An-/Abmeldung zur Prüfung Anm.: Belegen Lehrveranstaltung; Abm.: stornieren
Wiederholungsprüfung keine Wiederholungsprüfung
Skala 1-6 0,5
Belegen bei Nichtbestehen beliebig wiederholbar
Zuständige Fakultät Philosophisch-Naturwissenschaftliche Fakultät, studiendekanat-philnat@unibas.ch
Anbietende Organisationseinheit Fachbereich Informatik

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