Dr. Pascal Bercher

Research Area:
+61 (0)2 - 612 - 50 322


  • Nov. 2019 -- today: (tenure-track) Lecturer (Eng.: Assistance Professor) at ANU. I gave and probably will give several Guest Lectures on AI, Planning, and Games. Teaching-wise, my main responsibility is, however, teaching the Logic course, which I will co-deliver with (Lecturer) Yoshihiro (Yoshi) Maruyama.
  • Oct. 2016 -- Oct. 2019: Project coordinator (over the enture runtime) of the technology transfer project Do it yourself, but not alone: Companion-Technology for Home Improvement, which was a collaboration between two Institutes of Ulm University and the Corporate Research Sector of Robert Bosch GmbH.
  • July 2009 --  Dec. 2017: Dr. rer. nat. at the Institute of Artificial Intelligence of Ulm University, Germany. My supervisor was Prof. Dr. Susanne Biundo-Stephan.
  • Oct. 2003 -- June 2009: Studies of Computer Science (Diploma, which is roughly Bachelor + Master in one degree) at the University of Freiburg, Germany.


I am doing research in the fields of Hierarchical Task Network (HTN) Planning and Partial Order Causal Link (POCL) Planning. I'm interestested in theoretical foundations (mostly complexity analyses), algorithms, and heuristics of/for those fields. For a more detailed description of my research interests see the respective tab or check out some of my papers.

PhD under my Supervision:

  • Scholarships / Funding: I don't have any scholarships that I can hand out directly, but the school/college give/s out scholarships to the best of the best (the entire process takes time, so be patient). Thus, if you are a straight A / HD student (i.e., having only *very* good marks), then please reach out to me (otherwise it's probably not worth our time). If your profile fits my research expertise and interests, we can apply for such a scholarship -- and we might just be lucky. I would also be willing to supervise self-funded PhD students, but also then I only accept the best of the best. If in doubt, contact me!
  • Who can apply? My time is precious, so I will only accept straight A / HD students. You might be a bit weaker in courses that don't relate, but I expect that you can read and understand formalism-heavy scientific papers (eventually, clearly, you are no expert yet!). You will have to have basic background knowledge in related areas. Obviously, having attended courses like Artificial Intelligence (search, heuristics, planning etc.) would be invaluable, but also general computer science courses like Complexity Theory / Theory of Computation, or even Graph Theory could suffice. Just convince me that you have what it takes to be successful! I only have the highest expectations from anybody I supervise. But I will offer an for-me-unhealthy amount of supervision and guidance as payback. Also, my field is super-interesting, and there is a lot to explore, so take the opportunity!
  • How to apply? First of all, write your email with care, I do not want to see mistakes and carelessness. Don't worry if you are not perfect in writing (or speaking) English, I do not care about this! But I care about the effort you take. Even if you only speak relatively weak English, you should know where to place a dot when ending a sentence. You should know which words to capitalize, and by all means, after each dot and comma (etc.) there has to be a blank! Write a careless email and I will classify it as SPAM. Please skip the title, just call me Pascal. If you want to prove your respect towards me, do this by taking time for your email, not by "praising" (...) me or using titles. I will let you decide what to put into your application, but clearly I require a transcript and a few sentences about your background and why you would like to pursue a PhD (maybe more specific, i.e., why in planning). I might then give you a very few papers to read so we can have an interview about it. Pass that and we see further. Also, don't be afraid writing me! I'm a nice guy, seriously :), I just put these general guidelines here to save us all a bit of time.
  • Further information? Read the ANU PhD scholarship info page and some more information on ANU MPhil and PhD scholarships and applications.


  • ICAPS 2020, the 30th International Conference on Planning and Scheduling, goes online and is free! There are paper presentations, invited talks, tutorials, and workshops -- all online and free! One excerpt from an ICAPS mailing:
    The spirit of our design is to make the conference feel as much as a real ICAPS as possible. We even have a virtual version of the central place in Nancy (Place Stanislas), that you can walk over and sit down on!
    So please join us: https://icaps20.icaps-conference.org/index.html (Also if you are still a student, of course!)
  • I'm co-organizing the IPC 2020 together with Gregor Behnke and Daniel Höller, which evaluates the performance of domain-independent Hierarchical Task Network (HTN) planning.
  • I'm co-organizing HPlan 2020, the 3rd ICAPS workshop on hierarchical planning. It's online and free! (See above.)


Before I joined ANU I was also involved in teaching at two other Universities: University of Freiburg, Germany (where I was still a student) and at Ulm University, Germany, where I did my PhD and (almost) two years of post-doc.


  • In S1 of 2020, I acted as the assistant (together with Yoshihiro (Yoshi) Maruyama) to the lecture Logic (COMP2620/COMP6262/PHIL2080) by John Slaney.
  • In S1 of 2020, I held a guest lecture (2 hours, but stretched to 3 hours in the recordings to include more explanations) in the lecture Advanced Computing R&D Methods (COMP2550/4450/6445) by Jochen Renz. The lecture was on Theoretical Research Methods, with a focus on Heuristic Properties in Search and Classical Planning. Slides.
  • In S2 of 2020 I held a guestlecture on AI in Games in Steve Blackburn's lecture Structured Programming (COMP1110). Slides.

Ulm University

Lectures delivered:

  • In SS 2019 I delivered 5 lecture classes (25 % of the entire lecture) in the course Introduction to Computer Science.
  • In WS 2018/2019 I delivered a course on Hierarchical Planning that was conceptualized and delivered by myself.

Lectures supported:

I was supporting my colleagues in several AI planning and foundational AI lectures. The lectures listed below are only those which I was responsible for (which includes creating the exercises and exams as well as being a lecturer of the respective exercise classes).

  • Intelligent Planning (SS 18)
  • Intelligent Planning (WS 17/18)
  • Intelligent Planning (SS 17)
  • Introduction to Artificial Intelligence (WS 17/18)
  • Introduction to Artificial Intelligence (WS 13/14)
  • Introduction to Artificial Intelligence (WS 12/13)
  • Introduction to Artificial Intelligence (SS 10)

Seminars organized and supported:

I was a supervisor for one to three seminar participants in all of the following seminars:

Introductory Seminars:

  • Artificial Intelligence (SS 19) -- this seminar was organized by me
  • Artificial Intelligence (SS 18)
  • Artificial Intelligence (WS 17/18)
  • Artificial Intelligence (SS 17)
  • Artificial Intelligence (SS 16)
  • Artificial Intelligence (WS 15/16)
  • Artificial Intelligence (SS 15)
  • Artificial Intelligence (SS 13)
  • Artificial Intelligence (SS 12)


  • Advances in Artificial Intelligence (WS 17/18)
  • Advances in Artificial Intelligence (SS 17)
  • Artificial Companions (SS 16)
  • Advances in Artificial Intelligence (WS 13/14)
  • Advances in Artificial Intelligence (WS 12/13)
  • Advances in Artificial Intelligence (SS 12)

I did also do supervision:

  • 3 Diploma or Master Theses (Diploma Theses do not exist anymore, they are essentially the same as Master Theses). Master Theses are essentially the same as 24 point Honours research projects at ANU.
  • 9 Bachelor Theses. A Bachelor theses can be regarded a bit more than a 12 point research project at ANU.
  • 5 Projects and Practicals. These can differ severely in their length and can be compared with either 12 or even 24 point research projects at ANU. The major differences are that they are focused on programming something, so there does not need to be any scientific research involved. Secondly, students are only required to write a "report" rather than a "thesis", which is not nearly as scientific and long as a thesis required to be.

University of Freiburg

While I was still a student of Computer Science at the University of Freiburg, I was a tutor for several lectures. There, being a tutor implied correcting exercises (and exams, but don't tell! :)) and being a lecturer of the respective practice groups. These are the respective lectures:

  • Formal Methods and Programming (WS 08/09, Lecture of Cognitive Science)
  • Foundations of Artificial Intelligence (SS 08)
  • Foundations of Artificial Intelligence (SS 07)
  • Computer Science I (WS 05/06)

As my doctoral thesis, my research interestes span from theory to practice -- content-wise all is concerned with either Hierarchical Task Network (HTN) planning or Partial Order Causal Link (POCL) planning.

Hierarchical Task Network Planning

Short explanation of HTN planning: HTN planning is an approach to planning that's centered around problem decomposition. We are given an initial task network -- a partially ordered set of primitive or compound (or abstract) tasks. Primitive tasks are the actions known from classical planning, i.e. they specify preconditions and effects stating in which states they are applicable and how they chance a state if applied. Compound tasks are just abstracts of pre-defined task networks, so they are essentially just (parametrized) names like go(Canberra,Sydney). The planning model specifies rules how they can be achieved. These rules, called decomposition methods, are simply mappings to pre-defined task networks, which can in turn contain compound tasks. The goal is to refine the initial task netowork into a primitive one that is executable. HTN planning is more expressive than classical planning, where this mechanism of task decomposition does not exist. In its most general form (as just explained) it's undecidable.

My research interests in HTN planning are, roughly ordered by my interest:

  • Design of well-informed heuristics. (This is still a young field with only a limited number of heuristics availaible.)
  • Investigation of the computational complexity of various problems like the plan existence problem (how hard is it do decide whether there exists a solution?)
  • Essentially all questions that are related to incorporating human users into the loop. These comprise:
    • Plan abstraction and presentation (how can plans be presented on a more abstract level? can we stop planning on more abstract levels?)
    • Plan linearization and presentation (in which order should plan steps be presented to a human user so that the pan's execution order seems reasonable?)
    • Plan explanations (how to find reasonable explanations for plans and how they look like?)

Partial Order Causal Link (POCL) Planning

Short explanation of POCL planning: POCL planning is a technique for solving classical panning problems, where we would like to find a plan in order to achieve some (state-based) goals. In POCL planning, this is done in the space of partially ordered (also called non-linear) plans. Search is done in a regression-like fashion starting with the goals: select a condition not yet achieved (called "open") and select an appropriate action (i.e., with matching effect) from the plan or model and "document" that goal achievement by the insertion of a so-called causal link. Tis procedure is repeated until a goal plan has been found. Since search nodes are partially ordered plans (rather than states as in standard progression search), heuristic desingn is much more complicated.

Some mor ebackground of POCL planning: Since roughly 15 years this kind of problem solving is generally regarded outdated (some even say obsolete!) because state-based progression search is simply much more efficient nowadays. However, this argument is a purely empirial one. Moreover, there is a vast variety of well-informed heuristics in classical state-based planning, but almonst none exist in POCL planning. Hence, it's interesting to imagine where POCL could be by now if we had as well-informed heuristics for that search as well. (Whether this can even be is another question, as some of my theoretical results indicate that heuristic design is computationally harder than in the progression setting.) Another important note to make is that POCL techniques are still used in hierarchical planning, as one of the few standard techniques for solving HTN problems relies on POCL planning techniques.

My research interests in POCL planning are, roughly ordered my interest:

  • Design of well-informed heuristics. (Again, almos no heuristics exist so far!)
  • Investigation of the computational complexity related to POCL plans (such as the plan existence or plan opimization.)

Practical Application

Well, most that I am intersted in is already covered above as part of HTN planning: When ever one integrates a human into the loop, several new questions arise that need to be addressed in a systematic way. For instance, once we have found a solution to a problem (i.e., a plan) that plan can be executed successfully as otherwise it wouldn't be a solution. However, for a human it might be a big difference in which order its actions are executed (by him or her) since there might be a switch of contexts that could be confusing or even annoying. Finding a reasonable (we called it "user-friendly") reordering is one such task that can be investigated on both a formal and an empircal level. Other related questions, as mentioned above, are the presentation of plans on higher levels of abstraction and the explanation of plans.

Another important aspect in the practical application of planning technology is the planning language's level of expressiveness. In order to solve real-world problems, we need to be able to express time (at the least!) or more generally functions. This will require new formalisms, reductions, and heuristics.

You can also find me on Google Scholar and in DBLP




Book Chapters:



Conny Olz »

Best Paper Awards:

Best Reviewer Awards:

 To maintain anonymity, honours and awards for journals are listed at the end, in a meaningless order, without any year, probably severely outdated (also to maintain anonymity, like for journal reviewing).

  • AAAI 2019 Outstanding Program Committee Member
    Six out of 2201 program committee members (2.7 ‰) won this award.
  • Theoretical Computer Science Outstanding Reviewer Award (Elsevier journal)

Further Honours and Awards:

  • Cooperation Award: Science – Economy 2019
    The research project Do it yourself, but not alone: Companion-Technology for Home Improvement" that was coordinated by me for its entire runtime from 2016 to 2019 won Ulm University's "Cooperation Award: Science – Economy 2019" (German: Kooperationspreis: Wissenschaft – Wirtschaft 2019).
  • ICAPS 2019 Best Dissertation Award
    For my dissertation Hybrid Planning -- From Theory to Practice

    Award description from ICAPS website:
    The dissertation stands out by covering a lot of ground:
    1. It formalizes and develops planning with hierarchical task networks (HTNs) toward a hybrid formalism that includes partial-order causal link planning;
    2. it presents complexity results for the resulting problem classes;
    3. it develops heuristics for hybrid planning;
    4. it describes the implementation of a hybrid planner and its integration into a companion device that assists in the set-up of a home theater system; and
    5. it performs a user study to evaluate the system. The dissertation also rekindled interest in HTN planning by putting it on firm formal ground and connecting it to recent developments in classical planning.
  • Nomination for the GI Best Dissertation Award 2017
    Ulm University nominated my dissertation for the GI Best Dissertation Award 2017, a national award (joint with the GI Germany, Switzerland, and Austria) for the best dissertation in the field of Computer Science. The GI (Gesellschaft für Informatik, eng: Society for Computer Science) encourages nominations that make progress in the field of Computer Science or related practical-oriented areas; they should further have some impact on the today's society. The final winners were announced here. My 10-page dissertation abstract (in German), as well as all other nomitated dissertations, are published in the Proceedings "Ausgezeichnete Informatikdissertationen" (eng: Awarded Computer Science Dissertations).
  • Paper Presentation at Press Conference of AAAI 2015
    I was presenting my system demo paper "A Planning-based Assistance System for Setting Up a Home Theater" (AAAI 2015) at a press conference that was hold during the AAAI conference 2015. They selected five papers that are of interest to the public due to their relevance for today's society.



Reviewer for journals:
(Mostly severely outdated and years omitted -- both on purpose to maintain anonymity.)

  • Journal of Artificial Intelligence (JAIR)
    (1 article)
  • Theoretical Computer Science
    (1 article, awarded for outstanding reviewing)
  • IEEE Transactions on Systems, Man and Cybernetics: Systems
    (1 article)
  • KI – Künstliche Intelligenz
    (3 articles in a Special Issue on Companion Technologies for which I was a guest editor)

Reviewer for book chapters:

Senior Program Committee (SPC) member at conferences:

  • IJCAI: 2021
  • ICAPS: 2019

Program Committee (PC) member at conferences:

  • IJCAI: 2013, 2019–2020
  • IJCAI-ECAI: 2018
  • ECAI: 2020
  • AAAI: 2015, 2017–2019*, 2021
    (honored as outstanding PC member for AAAI 2019)

Program Committee (PC) member at workshops:

  • HPLAN, i.e., Hiearchical Planning: 2018-2020
  • XAIP, i.e., Explainable Planning: 2020

Reviewer for conferences (in addition to the PC/SPC memberships):

  • ICAPS: 2012, 2015–2018, 2020
  • ECAI: 2016
  • AAAI: 2012, 2014, 2020
  • KI: 2012–2013
  • SRC: 2020 (ANU's Student Research Conference)

Reviewer for workshops:

  • Computer Games Workshop: at IJCAI 2017


Invited Talks:

  • I gave a keynote speech about Companion Systems at the Digital Companion Workshop at MuC (Mensch und Computer; eng.: Human and Computer) 2018 in Dresden, Germany. Slides. Slides including embedded videos.
  • At KI 2017 I presented my 2017 IJCAI paper "An admissible HTN planning heuristic" in the "sister conference track".
  • In November 2017, I was invited to discuss the potentials and risks of AI in a so-called Junior Science Working Group of a high school in Fulda, Germany, in a plenum discussion together with other experts on the field (Prof. Dr. Gepperth, Prof. Dr. Winzerling, and Dr. Quarch).


Further services to the University and the AI community:

I use this page to make all downloads and links available that could be interesting and useful for some.

Hierarchical Planning

  • Tutorial on HTN planning by me and my former colleague Daniel Höller: link
  • A video explaining how Hierarchical Planning can be applied to realize assistance support for complex reasoning tasks -- illustrated with a system that supports in the task of setting up a home theater. All deployed technologies (such as hierarchical planning) get explained tailored to a general non-scientific audience: video

Classical Planning

  • Lecture slides introducing classical planning from scratch, focusing on heuristic search, one 2-hour lecture: download

AI in Games

  • Lecture slides on some basics in AI in Games, one 1-hour lecture: download. The lecture was recorded as well, and you can watch it here.


  • My LaTeX files for slides using beamer: download
    Note that this design does not comply with the ANU style guides.
  • Material for students who are new to doing scientific research and scientific writing. Specifically: A presentation about how to search for scientific papers and another one about writing a thesis (or seminar paper). An example seminar paper is given as well to provide an example on how to cite papers appropriately: download

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