On the Relevance of Extracting Macro-operators with Non-adjacent Actions: Does It Matter?

Sandra Castellanos-Paez; Romain Rombourg; Philippe Lalanda

doi:10.5220/0010305110211029

On the Relevance of Extracting Macro-operators with Non-adjacent Actions: Does It Matter?

Sandra Castellanos-Paez, Romain Rombourg, Philippe Lalanda

Grenoble Alps University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Understanding the role that plays the extraction phase on identifying potential macro candidates to augment a domain is critical. In this paper, we present a method to analyse the link between extracting macro-operators from non-adjacent actions and the correctness of (1) the frequency and (2) the number of occurrences per plan. We carried out experiments using our method on five benchmark domains and three different planners. We found that extracting macro-operators with only adjacent actions leads to important errors in macro-operator frequency and occurrences per plan.

Original language	English
Title of host publication	Proceedings of the 13th International Conference on Agents and Artificial Intelligence
Editors	Ana Paula Rocha, Luc Steels, Jaap van den Herik
Publisher	SciTePress
Pages	1021-1029
Number of pages	9
Volume	2
ISBN (Print)	9789897584848
DOIs	https://doi.org/10.5220/0010305110211029
Publication status	Published - 4 Feb 2021
Externally published	Yes
Event	13th International Conference on Agents and Artificial Intelligence - Online due to COVID-19 Duration: 4 Feb 2021 → 6 Feb 2021 Conference number: 13 http://www.icaart.org/Home.aspx

Publication series

Name	International Conference on Agents and Artificial Intelligence
Publisher	SciTePress
ISSN (Print)	2184-433X

Conference

Conference	13th International Conference on Agents and Artificial Intelligence
Abbreviated title	ICAART 2021
Period	4/02/21 → 6/02/21
Internet address	http://www.icaart.org/Home.aspx

Access to Document

10.5220/0010305110211029Licence: CC BY-NC-ND

Cite this

Castellanos-Paez, S., Rombourg, R., & Lalanda, P. (2021). On the Relevance of Extracting Macro-operators with Non-adjacent Actions: Does It Matter? In A. P. Rocha, L. Steels, & J. van den Herik (Eds.), Proceedings of the 13th International Conference on Agents and Artificial Intelligence (Vol. 2, pp. 1021-1029). (International Conference on Agents and Artificial Intelligence). SciTePress. https://doi.org/10.5220/0010305110211029

Castellanos-Paez, Sandra ; Rombourg, Romain ; Lalanda, Philippe. / On the Relevance of Extracting Macro-operators with Non-adjacent Actions : Does It Matter?. Proceedings of the 13th International Conference on Agents and Artificial Intelligence. editor / Ana Paula Rocha ; Luc Steels ; Jaap van den Herik. Vol. 2 SciTePress, 2021. pp. 1021-1029 (International Conference on Agents and Artificial Intelligence).

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abstract = "Understanding the role that plays the extraction phase on identifying potential macro candidates to augment a domain is critical. In this paper, we present a method to analyse the link between extracting macro-operators from non-adjacent actions and the correctness of (1) the frequency and (2) the number of occurrences per plan. We carried out experiments using our method on five benchmark domains and three different planners. We found that extracting macro-operators with only adjacent actions leads to important errors in macro-operator frequency and occurrences per plan. ",

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author = "Sandra Castellanos-Paez and Romain Rombourg and Philippe Lalanda",

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booktitle = "Proceedings of the 13th International Conference on Agents and Artificial Intelligence",

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note = "13th International Conference on Agents and Artificial Intelligence, ICAART 2021 ; Conference date: 04-02-2021 Through 06-02-2021",

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Castellanos-Paez, S, Rombourg, R & Lalanda, P 2021, On the Relevance of Extracting Macro-operators with Non-adjacent Actions: Does It Matter? in AP Rocha, L Steels & J van den Herik (eds), Proceedings of the 13th International Conference on Agents and Artificial Intelligence. vol. 2, International Conference on Agents and Artificial Intelligence, SciTePress, pp. 1021-1029, 13th International Conference on Agents and Artificial Intelligence, 4/02/21. https://doi.org/10.5220/0010305110211029

On the Relevance of Extracting Macro-operators with Non-adjacent Actions: Does It Matter? / Castellanos-Paez, Sandra; Rombourg, Romain; Lalanda, Philippe.
Proceedings of the 13th International Conference on Agents and Artificial Intelligence. ed. / Ana Paula Rocha; Luc Steels; Jaap van den Herik. Vol. 2 SciTePress, 2021. p. 1021-1029 (International Conference on Agents and Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Understanding the role that plays the extraction phase on identifying potential macro candidates to augment a domain is critical. In this paper, we present a method to analyse the link between extracting macro-operators from non-adjacent actions and the correctness of (1) the frequency and (2) the number of occurrences per plan. We carried out experiments using our method on five benchmark domains and three different planners. We found that extracting macro-operators with only adjacent actions leads to important errors in macro-operator frequency and occurrences per plan.

AB - Understanding the role that plays the extraction phase on identifying potential macro candidates to augment a domain is critical. In this paper, we present a method to analyse the link between extracting macro-operators from non-adjacent actions and the correctness of (1) the frequency and (2) the number of occurrences per plan. We carried out experiments using our method on five benchmark domains and three different planners. We found that extracting macro-operators with only adjacent actions leads to important errors in macro-operator frequency and occurrences per plan.

KW - Automated Planning

KW - Macro-operators

KW - Learning

KW - Data Mining

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Castellanos-Paez S, Rombourg R, Lalanda P. On the Relevance of Extracting Macro-operators with Non-adjacent Actions: Does It Matter? In Rocha AP, Steels L, van den Herik J, editors, Proceedings of the 13th International Conference on Agents and Artificial Intelligence. Vol. 2. SciTePress. 2021. p. 1021-1029. (International Conference on Agents and Artificial Intelligence). doi: 10.5220/0010305110211029

On the Relevance of Extracting Macro-operators with Non-adjacent Actions: Does It Matter?

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