Identifying and exploiting features for effective plan retrieval in case-based planning

Mauro Vallati; Ivan Serina; Alessandro Saetti; Alfonso E. Gerevini

Identifying and exploiting features for effective plan retrieval in case-based planning

Mauro Vallati, Ivan Serina, Alessandro Saetti, Alfonso E. Gerevini

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

Abstract

Case-Based planning can fruitfully exploit knowledge gained by solving a large number of problems, storing the corresponding solutions in a plan library and reusing them for solving similar planning problems in the future. Case-based planning is extremely effective when similar reuse candidates can be efficiently chosen. In this paper, we study an innovative technique based on planning problem features for efficiently retrieving solved planning problems (and relative plans) from large plan libraries. Since existing planning features are not always able to effectively distinguish between problems within the same planning domain, we introduce a new class of features. Our experimental analysis shows that the proposed features-based retrieval approach can significantly improve the performance of a state-of-theart case-based planning system.

Original language	English
Title of host publication	Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS 2015)
Editors	Ronen Brafman, Carmel Domshlak, Patrik Haslum, Shlomo Zilberstein
Publisher	AAAI press
Pages	239-243
Number of pages	5
ISBN (Electronic)	9781577357315
Publication status	Published - Apr 2015
Event	25th International Conference on Automated Planning and Scheduling - Jerusalem, Israel Duration: 7 Jun 2015 → 11 Jun 2015 Conference number: 25 http://icaps15.icaps-conference.org (Link to Conference Website )

Conference

Conference	25th International Conference on Automated Planning and Scheduling
Abbreviated title	ICAPS 2015
Country/Territory	Israel
City	Jerusalem
Period	7/06/15 → 11/06/15
Internet address	http://icaps15.icaps-conference.org (Link to Conference Website )

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https://www.aaai.org/ocs/index.php/ICAPS/ICAPS15/paper/view/10604Licence: Unspecified

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Vallati, M., Serina, I., Saetti, A., & Gerevini, A. E. (2015). Identifying and exploiting features for effective plan retrieval in case-based planning. In R. Brafman, C. Domshlak, P. Haslum, & S. Zilberstein (Eds.), Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS 2015) (pp. 239-243). AAAI press. https://www.aaai.org/ocs/index.php/ICAPS/ICAPS15/paper/view/10604

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title = "Identifying and exploiting features for effective plan retrieval in case-based planning",

abstract = "Case-Based planning can fruitfully exploit knowledge gained by solving a large number of problems, storing the corresponding solutions in a plan library and reusing them for solving similar planning problems in the future. Case-based planning is extremely effective when similar reuse candidates can be efficiently chosen. In this paper, we study an innovative technique based on planning problem features for efficiently retrieving solved planning problems (and relative plans) from large plan libraries. Since existing planning features are not always able to effectively distinguish between problems within the same planning domain, we introduce a new class of features. Our experimental analysis shows that the proposed features-based retrieval approach can significantly improve the performance of a state-of-theart case-based planning system.",

keywords = "case-based planning, planning features, plan retrieval",

author = "Mauro Vallati and Ivan Serina and Alessandro Saetti and Gerevini, {Alfonso E.}",

year = "2015",

month = apr,

language = "English",

pages = "239--243",

editor = "Ronen Brafman and Carmel Domshlak and Patrik Haslum and Shlomo Zilberstein",

booktitle = "Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS 2015)",

publisher = "AAAI press",

address = "United States",

note = "25th International Conference on Automated Planning and Scheduling, ICAPS 2015 ; Conference date: 07-06-2015 Through 11-06-2015",

url = "http://icaps15.icaps-conference.org",

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Vallati, M, Serina, I, Saetti, A & Gerevini, AE 2015, Identifying and exploiting features for effective plan retrieval in case-based planning. in R Brafman, C Domshlak, P Haslum & S Zilberstein (eds), Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS 2015). AAAI press, pp. 239-243, 25th International Conference on Automated Planning and Scheduling, Jerusalem, Israel, 7/06/15. <https://www.aaai.org/ocs/index.php/ICAPS/ICAPS15/paper/view/10604>

Identifying and exploiting features for effective plan retrieval in case-based planning. / Vallati, Mauro; Serina, Ivan; Saetti, Alessandro et al.

Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS 2015). ed. / Ronen Brafman; Carmel Domshlak; Patrik Haslum; Shlomo Zilberstein. AAAI press, 2015. p. 239-243.

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

TY - GEN

T1 - Identifying and exploiting features for effective plan retrieval in case-based planning

AU - Vallati, Mauro

AU - Serina, Ivan

AU - Saetti, Alessandro

AU - Gerevini, Alfonso E.

N1 - Conference code: 25

PY - 2015/4

Y1 - 2015/4

N2 - Case-Based planning can fruitfully exploit knowledge gained by solving a large number of problems, storing the corresponding solutions in a plan library and reusing them for solving similar planning problems in the future. Case-based planning is extremely effective when similar reuse candidates can be efficiently chosen. In this paper, we study an innovative technique based on planning problem features for efficiently retrieving solved planning problems (and relative plans) from large plan libraries. Since existing planning features are not always able to effectively distinguish between problems within the same planning domain, we introduce a new class of features. Our experimental analysis shows that the proposed features-based retrieval approach can significantly improve the performance of a state-of-theart case-based planning system.

AB - Case-Based planning can fruitfully exploit knowledge gained by solving a large number of problems, storing the corresponding solutions in a plan library and reusing them for solving similar planning problems in the future. Case-based planning is extremely effective when similar reuse candidates can be efficiently chosen. In this paper, we study an innovative technique based on planning problem features for efficiently retrieving solved planning problems (and relative plans) from large plan libraries. Since existing planning features are not always able to effectively distinguish between problems within the same planning domain, we introduce a new class of features. Our experimental analysis shows that the proposed features-based retrieval approach can significantly improve the performance of a state-of-theart case-based planning system.

KW - case-based planning

KW - planning features

KW - plan retrieval

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M3 - Conference contribution

AN - SCOPUS:84943254794

SP - 239

EP - 243

BT - Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS 2015)

A2 - Brafman, Ronen

A2 - Domshlak, Carmel

A2 - Haslum, Patrik

A2 - Zilberstein, Shlomo

PB - AAAI press

T2 - 25th International Conference on Automated Planning and Scheduling

Y2 - 7 June 2015 through 11 June 2015

ER -

Identifying and exploiting features for effective plan retrieval in case-based planning

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