The 2023 International Planning Competition

Open Access
Authors
  • D. FiĊĦer
  • M. Gimelfarb
  • F. Pommerening
  • S. Sanner
  • E. Scala
  • D. Schreiber
  • J. Segovia-Aguas
  • J. Seipp
Publication date 2024
Journal AI Magazine
Volume | Issue number 45 | 2
Pages (from-to) 280-296
Number of pages 17
Organisations
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract

In this article, we present an overview of the 2023 International Planning Competition. It featured five distinct tracks designed to assess cutting-edge methods and explore the frontiers of planning within these settings: the classical (deterministic) track, the numeric track, the Hierarchical Task Networks (HTN) track, the learning track, and the probabilistic and reinforcement learning track. Each of these tracks evaluated planning methodologies through one or more subtracks, with the goal of pushing the boundaries of current planner performance. To achieve this objective, the competition introduced a combination of well-established challenges and entirely novel ones. Within this article, each track offers an exploration of its historical context, justifies its relevance within the planning landscape, discusses emerging domains and trends, elucidates the evaluation methodology, and ultimately presents the results.

Document type Article
Note Meeting report
Language English
Published at https://doi.org/10.1002/aaai.12169
Other links https://www.scopus.com/pages/publications/85190366216
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