AI Planning

Prof. Dr. Jörg Hoffmann, Dr. Daniel Fišer, Daniel Gnad, Daniel Höller

Timetable

Title Type Location Serial Start End All Day
Lecture: About this course Lecture 19.10.21 19.10.21 No 
Lecture: PDDL; Applications Lecture 1 26.10.21 26.10.21 No 
Lecture: Progression and Regression; Heuristic Search Lecture 1 02.11.21 02.11.21 No 
Lecture: Delete Relaxation Heuristics Lecture 1 09.11.21 09.11.21 No 
Lecture: Delete Relaxation Heuristics Lecture 1 16.11.21 16.11.21 No 
Lecture: Partial Delete Relaxation; Abstractions Lecture 1 23.11.21 23.11.21 No 
Lecture: Abstractions; Pattern Database Heuristics Lecture 1 30.11.21 30.11.21 No 
Lecture: Merge-and-Shrink Heuristics Lecture 1 07.12.21 07.12.21 No 
Lecture: Landmark Heuristics Lecture 1 14.12.21 14.12.21 No 
Lecture: Planning Formalisms Lecture 2 20.10.21 20.10.21 No 
Lecture: Causal Graphs; Progression and Regression Lecture 2 27.10.21 27.10.21 No 
Lecture: Heuristic Search; Critical Path Heuristics Lecture 2 03.11.21 03.11.21 No 
Lecture: Partial Delete Relaxation Lecture 2 17.11.21 17.11.21 No 
Lecture: Pattern Database Heuristics Lecture 2 01.12.21 01.12.21 No 
Lecture: Partial-Order Reduction Lecture 2 08.12.21 08.12.21 No 
Lecture: Decoupled State Space Search Lecture 1 25.01.22 25.01.22 No 
Lecture: Combining Heuristic Functions Lecture 1 11.01.22 11.01.22 No 
Lecture: Comparing Heuristic Functions Lecture 2 12.01.22 12.01.22 No 
Lecture: Landmark Heuristics; Combining Heuristic Functions Lecture 2 05.01.22 05.01.22 No 
Lecture: Towards Trust in Neural Action Policies Lecture 26.01.22 26.01.22 No 
Lecture: Comparing Heuristic Functions; Decoupled State Space Search Lecture 18.01.22 18.01.22 No 
Lecture: Planning Systems and the IPC Lecture 01.02.22 01.02.22 No 
Tutorial 5 Tutorial 02.02.22 02.02.22 No 
Tutorial 1 Tutorial 10.11.21 10.11.21 No 
Tutorial 2 Tutorial 24.11.21 24.11.21 No 
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