[PlanetKR] Invitation to the AAAI-26 Tutorial “Domain Model Learning in AI Planning”

[Leonardo Lamanna]

Dear planning and learning enthusiasts,

We are pleased to invite you to attend the tutorial “Domain Model Learning
in AI Planning”, to be held at AAAI 2026 in Singapore EXPO on Wednesday,
January 21st (half-day), which covers the foundations, recent advances in
techniques and tools, and open challenges for automated domain-model
learning.

Automated planning heavily relies on the availability of planning domain
models that describe the environment dynamics. However, handcrafting such
models is widely known to be time-consuming, prone to errors, and to
require extensive knowledge about the environments. For these reasons, the
AI planning community has proposed several theories and algorithms that
automatically learn domain models.

The tutorial is aimed at researchers, practitioners, and students
interested in techniques for learning planning domain models. The objective
of this tutorial is to give participants a clear overview of
state-of-the-art methods for learning domain models under different
assumptions (e.g., partially or noisy observability), to enable them to
effectively use open-source frameworks and tools for domain-model learning,
and highlight open research challenges at the intersection of machine
learning and symbolic planning.

If you have any questions, please do not hesitate to contact us. Further
details about the tutorial are available on the tutorial and AAAI-2026
websites:

https://domain-learning.github.io

https://aaai.org/conference/aaai/aaai-26/tutorial-and-lab-list/#th17


We look forward to your participation in this AAAI-26 tutorial!

Organizing Committee:

Prof. Roni Stern, BGU

Prof. Christian Muise, Queen’s University

Dr. Leonardo Lamanna, FBK

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