Subject description - XP36APL

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XP36APL Automated Planning
Roles:  Extent of teaching:2P
Department:13136 Language of teaching:
Guarantors:Edelkamp S. Completion:ZK
Lecturers:Edelkamp S., Chrpa L. Credits:4
Tutors:Edelkamp S., Chrpa L. Semester:Z,L

Anotation:

The goal of the course is to provide comprehensive and detailed information about state-of-the-art methods in the area of symbolic artificial intelligence for automated planning. The students will learn about the classical, but also various extensions of, planning models and related knowledge engineering techniques; the most prevalent search methods, incl. variants of greedy best first search, hill climbing methods, and the A* algorithm in context of automated planning; and thorough description and implementation details of currently most efficient domain-independent heuristics. A student successfully passing the course will understand the principles of automated planning and symbolic AI for sequential decision making. Additionally, they will be equipped with enough knowledge to design and implement novel domain-specific and/or domain-independent heuristics not only in context of automated planning, but applicable generally in tasks.

Course outlines:

1. Introduction to Automated Planning
2. Classical and Extended Planning Models
3. Transformations Between the Planning Models
4. Knowledge Engineering and Modelling
5. Domain-Independent vs. Domain-Dependent Modeling
6. State Invariants
7. Heuristic State-Space Search
8. Relaxation Heuristics
9. Abstraction heuristics
10. Bisimulation and Symbolic Planning
11. Heuristics using LP formulations
12. Metric and Temporal Planning
13. Preferences and Hybrid Planning
14. Planners and Implementations

Exercises outline:

Literature:

* Malik Ghallab, Dana S. Nau, Paolo Traverso: Automated Planning and Acting. Cambridge University Press 2016, ISBN 978-1-107-03727-4 * Stefan Edelkamp, Stefan Schrödl: Heuristic Search - Theory and Applications. Academic Press 2012, ISBN 978-0-12-372512-7, pp. I_XXIV, 1-836 * Malik Ghallab, Dana S. Nau, Paolo Traverso: Automated planning - theory and practice. Elsevier 2004, ISBN 978-1-55860-856-6, pp. I-XXVIII, 1-635

Requirements:

Subject is included into these academic programs:

Program Branch Role Recommended semester


Page updated 28.4.2024 14:51:24, semester: Z,L/2023-4, Z/2024-5, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)