@article{hoeller-etal-21-PANDA,
title = {The PANDA Framework for Hierarchical Planning},
author = {Daniel H{\"o}ller and Gregor Behnke and Pascal Bercher and Susanne Biundo},
url = {https://link.springer.com/article/10.1007/s13218-020-00699-y},
doi = {https://doi.org/10.1007/s13218-020-00699-y},
year = {2021},
date = {2021},
journal = {K{\"u}nstliche Intelligenz},
abstract = {During the last years, much progress has been made in hierarchical planning towards domain-independent systems that come with sophisticated techniques to solve planning problems instead of relying on advice in the input model. Several of these novel methods have been integrated into the PANDA framework, which is a software system to reason about hierarchical planning tasks. Besides solvers for planning problems based on plan space search, progression search, and translation to propositional logic, it also includes techniques for related problems like plan repair, plan and goal recognition, or plan verifcation. These various techniques share a common infrastructure, like e.g. a standard input language or components for grounding and reachability analysis. This article gives an overview over the PANDA framework, introduces the basic techniques from a high level perspective, and surveys the literature describing the diverse components in detail.},
pubstate = {published},
type = {article}
}