The Benefit of Control Knowledge and Heuristics During Search in Planning

Jindřich Vodrážka, Roman Barták

2016

Abstract

The overall performance of classical planner depends heavily on the domain model which can be enhanced by adding control knowledge and heuristics. Both of them are known techniques which can boost the search process in exchange for some computational overhead needed for their repeated evaluation. Our experiments show that the gain from usage of heuristics and control knowledge is evolving throughout the search process and also depends on the type of search algorithm. We demonstrate the idea using the branch-and-bound and iterative deepening search techniques, both implemented in the Picat planning module.

Paper Citation

in Harvard Style

Vodrážka J. and Barták R. (2016). The Benefit of Control Knowledge and Heuristics During Search in Planning . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-172-4, pages 552-559. DOI: 10.5220/0005828005520559

in Bibtex Style

@conference{icaart16,
author={Jindřich Vodrážka and Roman Barták},
title={The Benefit of Control Knowledge and Heuristics During Search in Planning},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2016},
pages={552-559},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005828005520559},
isbn={978-989-758-172-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - The Benefit of Control Knowledge and Heuristics During Search in Planning
SN - 978-989-758-172-4
AU - Vodrážka J.
AU - Barták R.
PY - 2016
SP - 552
EP - 559
DO - 10.5220/0005828005520559