Participation

Please register for the course to gain access to the Adam workspace.

Lecture Slides

No.TopicDateSlides
A1Organizational Matters18.09.printer
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A2What is Planning?18.09.printer
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A3Getting to Know a Planner23.09.printer
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B1Transition Systems and Propositional Logic23.09.printer
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B2Introduction to Planning Tasks25.09.printer
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B3Formal Definition of Planning25.09.printer
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B4Equivalent Operators and Normal Forms30.09.printer
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B5Positive Normal Form and STRIPS30.09.printer
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B6Computational Complexity of Planning02.10.printer
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C1Overview of Classical Planning Algorithms07.10.printer
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C2Progression and Regression Search09.10.printer
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C3General Regression09.10.printer
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C4SAT Planning: Core Idea and Sequential Encoding14.10.printer
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C5SAT Planning: Parallel Encoding14.10.printer
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C6Symbolic Search: Binary Decision Diagrams16.10.printer
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C7Symbolic Search: Full Algorithm16.10.printer
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D1Delete Relaxation: Relaxed Planning Tasks21.10.printer
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D2Delete Relaxation: Properties of Relaxed Planning Tasks21.10.printer
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D3Delete Relaxation: Finding Relaxed Plans23.10.printer
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D4Delete Relaxation: AND/OR Graphs23.10.printer
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D5Delete Relaxation: Relaxed Task Graphs28.10.printer
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D6Delete Relaxation: hmax and hadd28.10.printer
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D7Delete Relaxation: Analysis of hmax and hadd30.10.printer
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D8Delete Relaxation: hFF and Comparison of Heuristics30.10.printer
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E1Planning Tasks in Finite-Domain Representation04.11.printer
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E2Invariants and Mutexes04.11.printer
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Extra Material

No.TitleFiles
B6Tom Bylander. The computational complexity of propositional STRIPS planning. Artificial Intelligence, 69(1-2), pp. 165-204, 1994.PDF
C1/D8Jörg Hoffmann and Bernhard Nebel. The FF Planning System: Fast Plan Generation Through Heuristic Search. Journal of Artificial Intelligence Research, 14, pp. 253-302, 2001.PDF
C1Silvia Richter and Matthias Westphal. The LAMA planner: Guiding cost-based anytime planning with landmarks. Journal of Artificial Intelligence Research, 39, pp. 127-177, 2010.PDF
C3Jussi Rintanen.Regression for Classical and Nondeterministic Planning. Proc. ECAI 2008, pp. 568-572, 2008.PDF
C5Jussi Rintanen, Keijo Heljanko, and Ilkka Niemelä.Planning as satisfiability: parallel plans and algorithms for plan search. Artificial Intelligence, 170(12-13), pp. 1031-1080, 2006.PDF
C7Álvaro Torralba. Symbolic Search and Abstraction Heuristics for Cost-Optimal Planning. PhD thesis, 2015.PDF
C7David Speck. Symbolic Search for Optimal Planning with Expressive Extensions. PhD thesis, 2022.PDF
D6Blai Bonet and Hector Geffner. Planning as Heuristic Search. Artificial Intelligence, 129(1), pp. 5-33, 2001.PDF
D8Emil Keyder and Hector Geffner. Heuristics for Planning with Action Costs Revisited. ECAI 2008, pp. 588-592, 2008.PDF
E1Jussi Rintanen. An Iterative Algorithm for Synthesizing Invariants. Proc. AAAI 2000, pp. 806-811, 2000.PDF
E2Daniel Fišer and Antonín Komenda. Fact-Alternating Mutex Groups for Classical Planning. Journal of Artificial Intelligence Research, 61, pp. 475-521, 2018.PDF