Generating predicate suggestions based on the space of plans: an example of planning with preferences

Task planning in human–robot environments tends to be particularly complex as it involves additional uncertainty introduced by the human user. Several plans, entailing few or various differences, can be obtained to solve the same given task. To choose among them, the usual least-cost plan criteria i...

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Detalles Bibliográficos
Autores: Canal, Gerard, Torras, Carme, Alenyà, Guillem
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/339499
Acceso en línea:http://hdl.handle.net/10261/339499
Access Level:acceso abierto
Palabra clave:Planning suggestions
Preference-based planning
Space of plans tree search
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spelling Generating predicate suggestions based on the space of plans: an example of planning with preferencesCanal, GerardTorras, CarmeAlenyà, GuillemPlanning suggestionsPreference-based planningSpace of plans tree searchTask planning in human–robot environments tends to be particularly complex as it involves additional uncertainty introduced by the human user. Several plans, entailing few or various differences, can be obtained to solve the same given task. To choose among them, the usual least-cost plan criteria is not necessarily the best option, because here, human constraints and preferences come into play. Knowing these user preferences is very valuable to select an appropriate plan, but the preference values are usually hard to obtain. In this context, we propose the Space-of-Plans-based Suggestions (SoPS) algorithms that can provide suggestions for some planning predicates, which are used to define the state of the environment in a task planning problem where actions modify the predicates. We denote these predicates as suggestible predicates, of which user preferences are a particular case. The first algorithm is able to analyze the potential effect of the unknown predicates and provide suggestions to values for these unknown predicates that may produce better plans. The second algorithm is able to suggest changes to already known values that potentially improve the obtained reward. The proposed approach utilizes a Space of Plans Tree structure to represent a subset of the space of plans. The tree is traversed to find the predicates and the values that would most increase the reward, and output them as a suggestion to the user. Our evaluation in three preference-based assistive robotics domains shows how the proposed algorithms can improve task performance by suggesting the most effective predicate values first.This work has been partially supported by the ERC project Clothilde (ERC-2016-ADG-741930); by MCIN/AEI/10.13039/501100011033 under the project CHLOE-GRAPH (PID2020-118649RB-l00); by the European Union NextGenerationEU/PRTR under the project ROB-IN (PLEC2021-007859); and by the CHIST-ERA project COHERENT (EPSRC EP/V062506/1). Gerard Canal has also been supported by the Spanish Ministry of Education, Culture and Sport by the FPU15/00504 doctoral grant and by the Royal Academy of Engineering and the Office of the Chief Science Adviser for National Security under the UK Intelligence Community Postdoctoral Research Fellowship programme.Peer reviewedKluwer Academic PublishersEuropean Research CouncilEuropean CommissionMinisterio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)Ministerio de Educación, Cultura y Deporte (España)Royal Academy of EngineeringConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2023202320232023info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/339499reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/741930info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-118649RB-I00info:eu-repo/grantAgreement/MECD//FPU15%2F00504info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PLEC2021-007859The underlying dataset has been published as supplementary material of the article in the publisher platform at http://dx.doi.org/10.1007/s11257-022-09327-whttp://dx.doi.org/10.1007/s11257-022-09327-wSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3394992026-05-22T06:33:51Z
dc.title.none.fl_str_mv Generating predicate suggestions based on the space of plans: an example of planning with preferences
title Generating predicate suggestions based on the space of plans: an example of planning with preferences
spellingShingle Generating predicate suggestions based on the space of plans: an example of planning with preferences
Canal, Gerard
Planning suggestions
Preference-based planning
Space of plans tree search
title_short Generating predicate suggestions based on the space of plans: an example of planning with preferences
title_full Generating predicate suggestions based on the space of plans: an example of planning with preferences
title_fullStr Generating predicate suggestions based on the space of plans: an example of planning with preferences
title_full_unstemmed Generating predicate suggestions based on the space of plans: an example of planning with preferences
title_sort Generating predicate suggestions based on the space of plans: an example of planning with preferences
dc.creator.none.fl_str_mv Canal, Gerard
Torras, Carme
Alenyà, Guillem
author Canal, Gerard
author_facet Canal, Gerard
Torras, Carme
Alenyà, Guillem
author_role author
author2 Torras, Carme
Alenyà, Guillem
author2_role author
author
dc.contributor.none.fl_str_mv European Research Council
European Commission
Ministerio de Ciencia, Innovación y Universidades (España)
Agencia Estatal de Investigación (España)
Ministerio de Educación, Cultura y Deporte (España)
Royal Academy of Engineering
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Planning suggestions
Preference-based planning
Space of plans tree search
topic Planning suggestions
Preference-based planning
Space of plans tree search
description Task planning in human–robot environments tends to be particularly complex as it involves additional uncertainty introduced by the human user. Several plans, entailing few or various differences, can be obtained to solve the same given task. To choose among them, the usual least-cost plan criteria is not necessarily the best option, because here, human constraints and preferences come into play. Knowing these user preferences is very valuable to select an appropriate plan, but the preference values are usually hard to obtain. In this context, we propose the Space-of-Plans-based Suggestions (SoPS) algorithms that can provide suggestions for some planning predicates, which are used to define the state of the environment in a task planning problem where actions modify the predicates. We denote these predicates as suggestible predicates, of which user preferences are a particular case. The first algorithm is able to analyze the potential effect of the unknown predicates and provide suggestions to values for these unknown predicates that may produce better plans. The second algorithm is able to suggest changes to already known values that potentially improve the obtained reward. The proposed approach utilizes a Space of Plans Tree structure to represent a subset of the space of plans. The tree is traversed to find the predicates and the values that would most increase the reward, and output them as a suggestion to the user. Our evaluation in three preference-based assistive robotics domains shows how the proposed algorithms can improve task performance by suggesting the most effective predicate values first.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/339499
url http://hdl.handle.net/10261/339499
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
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info:eu-repo/grantAgreement/EC/H2020/741930
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-118649RB-I00
info:eu-repo/grantAgreement/MECD//FPU15%2F00504
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PLEC2021-007859
The underlying dataset has been published as supplementary material of the article in the publisher platform at http://dx.doi.org/10.1007/s11257-022-09327-w
http://dx.doi.org/10.1007/s11257-022-09327-w
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Kluwer Academic Publishers
publisher.none.fl_str_mv Kluwer Academic Publishers
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
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