623.618 (24S) Current Topics in Planning and Scheduling
Überblick
- Lehrende/r
- LV-Titel englisch Current Topics in Planning and Scheduling
- LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
- LV-Modell Präsenzlehrveranstaltung
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 3.0
- Anmeldungen 14 (12 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- mögliche Sprache/n der Leistungserbringung Deutsch , Englisch
- LV-Beginn 18.03.2024
- eLearning zum Moodle-Kurs
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Anmerkungen
Die Online-Teilnahme an der Lehrveranstaltung wird über Moodle und BigBlueButton ermöglicht.
Zeit und Ort
LV-Beschreibung
Intendierte Lernergebnisse
Students are able to represent typical planning problems in general formalisms like PDDL, understand the computational methods, particular advantages as well as disadvantages of common planning systems.
Lehrmethodik
Practical exercises and projects based on the concepts introduced in lecture sessions
Inhalt/e
The course presents basic and advanced concepts of modern general-purpose planning systems, ranging from algorithmic methods and translation techniques to scheduling aspects. Topics to investigate include representation formalisms for expressing planning problems, such as the planning domain definition language (PDDL). We will inspect and exercise complementary solving algorithms and heuristics of corresponding domain-independent planning systems, which utilize state-space search methods or translate planning problems into constraint-based formalisms like ASP, CSP and SAT.
Erwartete Vorkenntnisse
Basic knowledge of propositional and first-order logic as well as fundamental concepts of artificial intelligence, knowledge representation and reasoning
Literatur
- Haslum, P., Lipovetzky, N., Magazzeni, D., Muise, C.: An Introduction to the Planning Domain Definition Language. Morgan and Claypool, 2019.
- Helmert, M.: The Fast Downward Planning System. Journal of Artificial Intelligence Research 26: 191–246, 2006.
- Dimopoulos, Y., Gebser, M., Lühne, P., Romero, J., Schaub, T.: plasp 3: Towards Effective ASP Planning. Theory and Practice of Logic Programming 19(3): 477-504, 2019.
- Rintanen, J.: Planning as Satisfiability: Heuristics. Artificial Intelligence 193: 45-86, 2012.
- Gebser, M., Kaminski, R., Kaufmann, B., Schaub, T.: Answer Set Solving in Practice. Morgan and Claypool, 2012.
Prüfungsinformationen
Prüfungsmethode/n
three practical assignments using domain-independent planning systems
Prüfungsinhalt/e
modeling and solving of planning problems based on the planning domain definition language
Beurteilungskriterien/-maßstäbe
correctness and comprehensiveness of supplied solutions to practical tasks
Beurteilungsschema
Note BenotungsschemaPosition im Curriculum
- Bachelorstudium Angewandte Informatik
(SKZ: 511, Version: 19W.2)
-
Fach: Artificial Intelligence and Natural Language Processing
(Wahlfach)
-
8.1 Artificial Intelligence and Natural Language Processing (
0.0h XX / 12.0 ECTS)
- 623.618 Current Topics in Planning and Scheduling (2.0h VC / 3.0 ECTS) Absolvierung im 4., 5., 6. Semester empfohlen
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8.1 Artificial Intelligence and Natural Language Processing (
0.0h XX / 12.0 ECTS)
-
Fach: Artificial Intelligence and Natural Language Processing
(Wahlfach)
- Bachelorstudium Robotics and Artificial Intelligence
(SKZ: 295, Version: 22W.1)
-
Fach: Robotics & AI Applications
(Wahlfach)
-
8.1 Robotics & AI Applications (
0.0h VO, VC, UE, KS / 12.0 ECTS)
- 623.618 Current Topics in Planning and Scheduling (2.0h VC / 3.0 ECTS)
-
8.1 Robotics & AI Applications (
0.0h VO, VC, UE, KS / 12.0 ECTS)
-
Fach: Robotics & AI Applications
(Wahlfach)