Automated Planning and Acting

Held in winter 21, winter 23, summer 26, planned: winter 27

Overview

This lecture presents methods of automated planning and acting, ranging range from deterministic and temporal methods to non-deterministic and probabilistic methods. Next to those methods, this lecture covers decision theory as the basis for probabilistic methods and also take a look at the most recent developments such as provably beneficial acting and human-aware planning.

The course is set up such that no prior knowledge is necessary. Nonetheless, it is beneficial to have a good grasp of search algorithms and a basic understanding of probability theory as certain formalisations might not look as foreign if you are familiar with those.

For the exercise, the plan is to have a seminar-style exercise with each person (or team if the number of participants gets too large) getting a topic to discover on their own and present to their peers. This presentation doubles as the prerequisite for admission to the final exam. The final exam will be an oral exam, bar a different announcement during the first lecture, depending on the number of participants.

Please register in the Learnweb course for more details and material.

Presentation Material (preliminary)

The slides used in the lecture always evolve a little bit. The following agenda links the most recent version. In older Learnweb courses you may find older version no longer linked here.

  1. Introduction (pptx, pdf)
  2. Planning and Acting with Deterministic Models (pptx, pdf)
  3. Planning and Acting with Refinement Methods (pptx, pdf)
  4. Planning and Acting with Temporal Models (pptx, pdf)
  5. Planning and Acting with Nondeterministic Models (pptx, pdf)
  6. Planning and Acting with Probabilistic Models (pptx, pdf)
  7. Planning and Acting by Decision Making
    1. Foundations (pptx, pdf)
    2. Extensions (pptx, pdf)
    3. Structure (pptx, pdf; not yet complete)
  8. Human-aware Planning (pptx, pdf)

Literature

  • Automated Planning and Acting, Malik Ghallab, Dana Nau, Paolo Traverso (mainly for Topics 1-5)
  • Artificial Intelligence: A Modern Approach (3rd edition, Chs. 16, 17, 21), Stuart Russell, Peter Norvig (mainly for Topics 6a and part of 6b)
  • A Concise Introduction to Decentralised POMDP, Frans A. Oliehoek, Christopher Amato (mainly for part of Topic 6b)

  • Explainable Human-AI Interaction: A Planning Perspective, Sarath Sreedharan, Anagha Kulkarni, Subbarao Kambhampati (mainly for Topic 7)

  • Further sources in the form of conference papers / articles as marked on slides