Loading…
FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning
Temporal planning offers numerous advantages when based on an expressive representation. Timelines have been known to provide the required expressiveness but at the cost of search efficiency. We propose here a temporal planner, called FAPE, which supports many of the expressive temporal features of...
Saved in:
Published in: | arXiv.org 2020-10 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | |
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Bit-Monnot, Arthur Ghallab, Malik Ingrand, Félix Smith, David E |
description | Temporal planning offers numerous advantages when based on an expressive representation. Timelines have been known to provide the required expressiveness but at the cost of search efficiency. We propose here a temporal planner, called FAPE, which supports many of the expressive temporal features of the ANML modeling language without loosing efficiency. FAPE's representation coherently integrates flexible timelines with hierarchical refinement methods that can provide efficient control knowledge. A novel reachability analysis technique is proposed and used to develop causal networks to constrain the search space. It is employed for the design of informed heuristics, inference methods and efficient search strategies. Experimental results on common benchmarks in the field permit to assess the components and search strategies of FAPE, and to compare it to IPC planners. The results show the proposed approach to be competitive with less expressive planners and often superior when hierarchical control knowledge is provided. FAPE, a freely available system, provides other features, not covered here, such as the integration of planning with acting, and the handling of sensing actions in partially observable environments. |
format | article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2454518543</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2454518543</sourcerecordid><originalsourceid>FETCH-proquest_journals_24545185433</originalsourceid><addsrcrecordid>eNqNi80KgkAUhYcgSMp3uNBa0PkpaReiuZRwLzcda8RmbGbs-ZPoAVqd7_CdsyIBZSyJUk7phoTODXEc08ORCsECci3OVX4ChMxo5y0q7aMbOtlBNaLW0kJvLFzkQujVWwLqDkq1NNs-VIsj1PI5GbvA96D0fUfWPY5Ohr_ckn2R11kZTda8Zul8M5jZ6kU1lAsuklRwxv5bfQBbTT7f</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2454518543</pqid></control><display><type>article</type><title>FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning</title><source>Publicly Available Content (ProQuest)</source><creator>Bit-Monnot, Arthur ; Ghallab, Malik ; Ingrand, Félix ; Smith, David E</creator><creatorcontrib>Bit-Monnot, Arthur ; Ghallab, Malik ; Ingrand, Félix ; Smith, David E</creatorcontrib><description>Temporal planning offers numerous advantages when based on an expressive representation. Timelines have been known to provide the required expressiveness but at the cost of search efficiency. We propose here a temporal planner, called FAPE, which supports many of the expressive temporal features of the ANML modeling language without loosing efficiency. FAPE's representation coherently integrates flexible timelines with hierarchical refinement methods that can provide efficient control knowledge. A novel reachability analysis technique is proposed and used to develop causal networks to constrain the search space. It is employed for the design of informed heuristics, inference methods and efficient search strategies. Experimental results on common benchmarks in the field permit to assess the components and search strategies of FAPE, and to compare it to IPC planners. The results show the proposed approach to be competitive with less expressive planners and often superior when hierarchical control knowledge is provided. FAPE, a freely available system, provides other features, not covered here, such as the integration of planning with acting, and the handling of sensing actions in partially observable environments.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Heuristic methods ; Representations ; Search methods</subject><ispartof>arXiv.org, 2020-10</ispartof><rights>2020. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2454518543?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>780,784,25752,37011,44589</link.rule.ids></links><search><creatorcontrib>Bit-Monnot, Arthur</creatorcontrib><creatorcontrib>Ghallab, Malik</creatorcontrib><creatorcontrib>Ingrand, Félix</creatorcontrib><creatorcontrib>Smith, David E</creatorcontrib><title>FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning</title><title>arXiv.org</title><description>Temporal planning offers numerous advantages when based on an expressive representation. Timelines have been known to provide the required expressiveness but at the cost of search efficiency. We propose here a temporal planner, called FAPE, which supports many of the expressive temporal features of the ANML modeling language without loosing efficiency. FAPE's representation coherently integrates flexible timelines with hierarchical refinement methods that can provide efficient control knowledge. A novel reachability analysis technique is proposed and used to develop causal networks to constrain the search space. It is employed for the design of informed heuristics, inference methods and efficient search strategies. Experimental results on common benchmarks in the field permit to assess the components and search strategies of FAPE, and to compare it to IPC planners. The results show the proposed approach to be competitive with less expressive planners and often superior when hierarchical control knowledge is provided. FAPE, a freely available system, provides other features, not covered here, such as the integration of planning with acting, and the handling of sensing actions in partially observable environments.</description><subject>Heuristic methods</subject><subject>Representations</subject><subject>Search methods</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNqNi80KgkAUhYcgSMp3uNBa0PkpaReiuZRwLzcda8RmbGbs-ZPoAVqd7_CdsyIBZSyJUk7phoTODXEc08ORCsECci3OVX4ChMxo5y0q7aMbOtlBNaLW0kJvLFzkQujVWwLqDkq1NNs-VIsj1PI5GbvA96D0fUfWPY5Ohr_ckn2R11kZTda8Zul8M5jZ6kU1lAsuklRwxv5bfQBbTT7f</recordid><startdate>20201025</startdate><enddate>20201025</enddate><creator>Bit-Monnot, Arthur</creator><creator>Ghallab, Malik</creator><creator>Ingrand, Félix</creator><creator>Smith, David E</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20201025</creationdate><title>FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning</title><author>Bit-Monnot, Arthur ; Ghallab, Malik ; Ingrand, Félix ; Smith, David E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_24545185433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Heuristic methods</topic><topic>Representations</topic><topic>Search methods</topic><toplevel>online_resources</toplevel><creatorcontrib>Bit-Monnot, Arthur</creatorcontrib><creatorcontrib>Ghallab, Malik</creatorcontrib><creatorcontrib>Ingrand, Félix</creatorcontrib><creatorcontrib>Smith, David E</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bit-Monnot, Arthur</au><au>Ghallab, Malik</au><au>Ingrand, Félix</au><au>Smith, David E</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning</atitle><jtitle>arXiv.org</jtitle><date>2020-10-25</date><risdate>2020</risdate><eissn>2331-8422</eissn><abstract>Temporal planning offers numerous advantages when based on an expressive representation. Timelines have been known to provide the required expressiveness but at the cost of search efficiency. We propose here a temporal planner, called FAPE, which supports many of the expressive temporal features of the ANML modeling language without loosing efficiency. FAPE's representation coherently integrates flexible timelines with hierarchical refinement methods that can provide efficient control knowledge. A novel reachability analysis technique is proposed and used to develop causal networks to constrain the search space. It is employed for the design of informed heuristics, inference methods and efficient search strategies. Experimental results on common benchmarks in the field permit to assess the components and search strategies of FAPE, and to compare it to IPC planners. The results show the proposed approach to be competitive with less expressive planners and often superior when hierarchical control knowledge is provided. FAPE, a freely available system, provides other features, not covered here, such as the integration of planning with acting, and the handling of sensing actions in partially observable environments.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2020-10 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2454518543 |
source | Publicly Available Content (ProQuest) |
subjects | Heuristic methods Representations Search methods |
title | FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T15%3A07%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=FAPE:%20a%20Constraint-based%20Planner%20for%20Generative%20and%20Hierarchical%20Temporal%20Planning&rft.jtitle=arXiv.org&rft.au=Bit-Monnot,%20Arthur&rft.date=2020-10-25&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2454518543%3C/proquest%3E%3Cgrp_id%3Ecdi_FETCH-proquest_journals_24545185433%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2454518543&rft_id=info:pmid/&rfr_iscdi=true |