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45400-01 - Vorlesung: Planning and Optimization 8 KP

Semester Herbstsemester 2024
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

 

Teilnahmebedingungen 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

Einzeltermine

Datum Zeit Raum
Montag 16.09.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 18.09.2024 14.15-16.00 Uhr --, --
Montag 23.09.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 25.09.2024 14.15-16.00 Uhr --, --
Montag 30.09.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 02.10.2024 14.15-16.00 Uhr --, --
Montag 07.10.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 09.10.2024 14.15-16.00 Uhr --, --
Montag 14.10.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 16.10.2024 14.15-16.00 Uhr --, --
Montag 21.10.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 23.10.2024 14.15-16.00 Uhr --, --
Montag 28.10.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 30.10.2024 14.15-16.00 Uhr --, --
Montag 04.11.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 06.11.2024 14.15-16.00 Uhr --, --
Montag 11.11.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 13.11.2024 14.15-16.00 Uhr --, --
Montag 18.11.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 20.11.2024 14.15-16.00 Uhr --, --
Montag 25.11.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 27.11.2024 14.15-16.00 Uhr --, --
Montag 02.12.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 04.12.2024 14.15-16.00 Uhr --, --
Montag 09.12.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 11.12.2024 14.15-16.00 Uhr --, --
Montag 16.12.2024 14.15-16.00 Uhr Spiegelgasse 1, Seminarraum 00.003
Mittwoch 18.12.2024 14.15-16.00 Uhr --, --
Module Doktorat Informatik: Empfehlungen (Promotionsfach: Informatik)
Modul: Applications of Distributed Systems (Masterstudium: Computer Science)
Modul: Concepts of Machine Intelligence (Masterstudium: Computer Science)
Modul: Concepts of Machine Intelligence (Master Studienfach: Computer Science)
Modul: Electives in Data Science (Masterstudium: Data Science)
Modul: Methods of Machine Intelligence (Masterstudium: Computer Science)
Leistungsüberprüfung Lehrveranst.-begleitend
Hinweise zur Leistungsüberprüfung 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 24, 2024, 2-4 p.m.

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

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