AI Planning Prof. Dr. Jörg Hoffmann


The course consists of oral lectures accompanied by programming exercises. Successful participation in the course yields 9 ECTS.

The course has two weekly slots of 90 minutes each, Tuesdays 12:15 -- 13:45, and Wednesdays 10:15 -- 11:45. Some slots are used for tutorials on paper exercises (see calendar below). Once every week, there will be office hours for the programming exercises.

The lectures will take place in Building E1 3, HS003. The tutorials and programming workshops will take place either in that same room, or at the FAI offices (Building E1 1, room 3.06). Exact details will be announced in the course management system.

The lectures will be given by Prof. Joerg Hoffmann and Dr. Alvaro Torralba, the tutorials will be given by Daniel Gnad. All lectures and tutorials will be held in English. For organizational issues please contact Maximilian Fickert.

Exercises and ECTS. The course will be accompanied by two kinds of exercises, paper exercises and programming exercises. The programming exercises are split into two parts. For the first part, you have to solve two projects individually. For the remaining projects, you are allowed to form groups of up to three students. To qualify for the exam, you need to obtain 50% from the individual programming exercises as well as 50 points from the programming exercises overall. (If you want to participate in future editions of this course, then you need to qualify anew; see also below.)

The paper exercises will involve applying the introduced concepts and algorithms to examples, and leading simple proofs. The paper exercise sheets will be handed out roughly in a biweekly cycle, i.e., in 2-week intervals. While the paper exercises are not mandatory to pass the course, they feature exercises similar to those in the exam so we highly recommend you try to solve them before the corresponding tutorials.

The programming exercises will involve implementing some of the techniques discussed, starting from a code base (essentially the Fast Downward planning system, FD, implemented in C++) we will provide. In other words, you will build your own planning system as part of the course! We'll run a competition among these systems at the end of term. To further motivate the programming work, good performance in the programming can help you in getting a good exam grade (see below).

Furthermore, in the programming exercises, you will be given the choice of which techniques to implement: Instead of fixed programming tasks on regular sheets, you will obtain a list of programming options up front. Each "option" here is one technique from the course, along with: the number of points obtained by implementing that technique; the time point in the course at which the technique will be explained; the dependencies with other options; and the deadline for submitting your solution if you choose to implement the option. The latter deadlines are also listed in the calendar.

The tutorial sessions will be classical tutorials discussing the solutions to the already solved paper exercises.

A tip: To get started on the planning modeling language PDDL, a good idea may be to have a look at this archive with example files, or import some benchmarks in the editor.

Exam and final grade. There will be a written exam at the end of the course. The final grade will be determined based on the performance in that exam, and the performance in the exercises.

For admission to the exam, you need to get at least 50% from the individual programming exercises as well as 50 points from the programming exercises overall.

The final grade will be determined based on a combination of your performance in the programming exercises and exam. Precisely, let N be your number of points in the exam itself, and M be your number of points in the programming exercises. To pass the exam, N>=50 is required. Your grade will be determined from max(N, 0.5*N + 0.5*min(M,110)). In other words, your grade results from either your exam performance, or from a weighted sum over exam and programming exercises (the latter being reduced to 110 points in case you got more than 110 points in those exercises).

Depending on the outcome of the 1st exam, there may be a 2nd exam end of March/beginning of April. If so, then, in compliance with the study regulations each of the two exams will count as a separate attempt to pass the course. In particular, the grading rule for each exam (separately) will be as just explained.

ATTENTION! The re-exam is your only chance to improve your grade.

  • By the study regulations, if you do not pass this edition of the course (if you fail, or are absent, in both the exam and the re-exam), then you can participate in future editions of the course as additional attempts to pass the course. (In this case, you need to qualify anew for the exam of that edition of the course.)
  • If you do pass this edition of the course, then you cannot improve your grade anymore. The only exception to the latter is if you already pass the exam: in that case, you can try to improve your grade in the re-exam.

Course Material. Due to the recency of the material covered, there exists no text book for this course. There are two kinds of slides, pre-handouts and post-handouts. Pre-handouts do not contain the answers to questions asked during the lecture sessions, and do not contain the details for examples worked during the lecture sessions. The post-handouts do contain all this, and correct any bugs. The pre-handouts are made available one day before the lecture sessions on each chapter, the post-handouts are made available directly after the lecture sessions on a chapter are finished.

Course Overview. The following table provides the provisional timing for the course. ATTENTION: Items displayed in red and blue deviate from the regular lecture days/times. See also the calendar here.

Date Lecturer Chapter(s) / Tutorials Exercise Deadlines
Tue 15.10 Hoffmann About this course  
Wed 16.10 Hoffmann Planning Formalisms  
Tue 22.10 Hoffmann PDDL; Applications Paper Exercise Handout: Sheet 1
Wed 23.10 Hoffmann Causal Graphs; Progression and Regression  
Tue 29.10 Hoffmann Progression and Regression; Heuristic Search  
Wed 30.10 Hoffmann Heuristic Search; Critical Path Heuristics  
Thu 31.10 Ferber Programming Workshop  
Tue 05.11 Torralba Delete Relaxation Heuristics Mon 04.11. Deadline: Goal Counting
Wed 06.11 Gnad Tutorial 1 Paper Exercise Handout: Sheet 2
Tue 12.11 Hoffmann Delete Relaxation Heuristics  
Wed 13.11 Hoffmann Partial Delete Relaxation  
Tue 19.11 Hoffmann Partial Delete Relaxation; Abstractions  
Wed 20.11 Gnad Tutorial 2  
Tue 26.11 Torralba Abstractions; Pattern Database Heuristics Mon 25.11. Deadline: hmax, hadd
Wed 27.11 Torralba Pattern Database Heuristics Thu 28.11 Deadline: Project Groups
Tue 03.12 Hoffmann Merge-and-Shrink Heuristics  
Wed 04.12 Hoffmann Partial-Order Reduction Paper Exercise Handout: Sheet 3
Tue 10.12 Hoffmann Landmark Heuristics Mon 09.12. Deadline: hFF
Wed 11.12 Hoffmann Landmark Heuristics; Combining Heuristic Functions  
Tue 17.12 Hoffmann Combining Heuristic Functions Mon 16.12. Deadline: h2, EHC
Wed 18.12 Gnad; Hoffmann Tutorial 3; Christmas Surprise Lecture Paper Exercise Handout: Sheet 4
    Christmas Break  
Tue 07.01   FREE Mon 06.01. Deadline: PDBs, M&S, RB
Wed 08.01 Hoffmann Comparing Heuristic Functions  
Tue 14.01 Hoffmann Comparing Heuristic Functions; Seach Space Surface Analysis Mon 13.01. Deadline: POR, LM, HA
Wed 15.01 Gnad Tutorial 4 Paper Exercise Handout: Sheet 5
Tue 21.01 Hoffmann Seach Space Surface Analysis Mon 20.01. Deadline: LMcut
Wed 22.01 Hoffmann Planning Systems and the IPC Thu 23.01. Deadline: Competition (prelim.)
Tue 28.01 Gnad Students' Planning Systems Competition Sun 26.01. Deadline: Competition (final)
Wed 29.01 Gnad Tutorial 5  
Tue 04.02   Exam Preparation  
Tue 11.02   Exam  

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