PhD Project: Various topics From Theory to Practice in Hierarchical Planning

Description

Hierarchical Planning is a planning formalism that's concerned with the step-wise refinement of abstract tasks until a primitive plan is found -- so hierarchical planning is very similar to formal grammars, where an initial non-terminal symbol is refined into a sequence of terminal symbols. The main differences are that (a) primitive tasks (corresponding to terminal symbols) have preconditions and effects, to not every plan is executable and (b) the means to refine compound tasks (which correspond to production rules from formal grammars) are only partially ordered rather than totally as in formal grammars.

I offer various PhD scholarships in the general area of Hierarchical Planning. In case you are interested please contact me and, in case of serious interest, make an appointment.

There are several opportunities to pursue a PhD related but not limited to:

  • Theoretical investigations related to hierarchical planning, most notably complexity investigations
  • Plan generation: Design of novel or improvement of existing planning techniques
  • Heuristic search: Development of novel heuristics for hierarchical planning
  • Learning models for hierarchical planning
  • Human-in-the-loop planning: various problems related to planning for or with humans, such as generating plan explanations, to name just one example

Goals

Depend on the concrete topic chosen.

Requirements

  • A solid understanding of theoretical computer science (e.g., of the classes P, NP, NP-complete, etc.) is helpful or even required for most topics, but definitely not for all of them
  • Prior knowledge in Classical Planning and/or Artificial Intelligence search (such as A*) will definitely be advantageous, but it's not strictly required

Background Literature

  • Pascal Bercher, Ron Alford, Daniel Höller: A Survey on Hierarchical Planning – One Abstract Idea, Many Concrete Realizations. IJCAI 2019, p.6267-6275. ijcai.org
  • Further literature depends on the chosen topic.

Gain

Depends on the concrete topic chosen.

Keywords

  • Complexity Theory
  • Artificial Intelligence
  • Automated Planning

Updated:  1 June 2019/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing