Contingent Planning in Domains with Unsafe Facts

Contingent Planning in Domains with Unsafe Facts | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Contingent Planning in Domains with Unsafe Facts Tomer Ravkaie, Guy Shani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7536680/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Contingent planning problems model agents with partial information about their state, that can use sensing actions to observe and reason about unknown values. Such problems can be efficiently solved using an online approach, where the agent replans each time new information is obtained through sensing.In this paper, we study Unsafe PPOS (U-PPOS) problems, where the input specification may contain unsafe facts—facts whose assumed value in the model differs from reality. Specifically, we consider false positives (FPs), which are assumed true but are actually false, and false negatives (FNs), which are assumed false but are actually true. FPs may lead planners to action failures, while FNs may cause the agent to believe that deadends exist. We propose methods to detect and handle both types of inaccuracies, establish their theoretical properties, and evaluate their performance across a set of benchmark domains. Contingent Planning Unsafe Facts Action Failures Deadends PPOS Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7536680","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":513294394,"identity":"1654ca5b-f8f6-4f8b-b57b-4029d5c8e1ea","order_by":0,"name":"Tomer Ravkaie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYDADfgh1AMo1sMCpkgfGkGwAa4BrkSCsxeAAihYG3Frs2bsTH1fusUvcfLv58OcPDHfsNhxgfviBoQCPLTxnNxueeZacuO3OsTSJAwzPkjccYDOWwOswidxtkg0HmI3NbuSYAZ11OBnoQjP8fpHI3f6z4UC9sfGMHOMPEC3s3whp2cbYcOCwnIFEjgHQYYftDA7wELDlzNnNQIcdl5MA+eWMwbMEycM8xRIJeLSwt/du/NhwoJqHf3bz4Q8VFXfs+Y63b/zw4Y8NTi0IADbWgCGxgRlIJxChAR539kQpHgWjYBSMghEFABoIVKoYosDMAAAAAElFTkSuQmCC","orcid":"","institution":"Ben-Gurion University of the Negev","correspondingAuthor":true,"prefix":"","firstName":"Tomer","middleName":"","lastName":"Ravkaie","suffix":""},{"id":513294395,"identity":"57a86fc5-1596-4e20-9025-a57319367722","order_by":1,"name":"Guy Shani","email":"","orcid":"","institution":"Ben-Gurion University of the Negev","correspondingAuthor":false,"prefix":"","firstName":"Guy","middleName":"","lastName":"Shani","suffix":""}],"badges":[],"createdAt":"2025-09-04 13:38:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7536680/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7536680/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100580217,"identity":"ce043d0d-bcf5-4382-ad9b-4b33b1f92342","added_by":"auto","created_at":"2026-01-19 11:06:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":808533,"visible":true,"origin":"","legend":"","description":"","filename":"JAAMASContingentPlanninginInaccurateDomains.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7536680/v1_covered_c22c973d-b2c6-4243-bd07-3cb6e1fbbf75.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contingent Planning in Domains with Unsafe Facts","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Contingent Planning, Unsafe Facts, Action Failures, Deadends, PPOS","lastPublishedDoi":"10.21203/rs.3.rs-7536680/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7536680/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Contingent planning problems model agents with partial information about their state, that can use sensing actions to observe and reason about unknown values. Such problems can be efficiently solved using an online approach, where the agent replans each time new information is obtained through sensing.In this paper, we study Unsafe PPOS (U-PPOS) problems, where the input specification may contain unsafe facts—facts whose assumed value in the model differs from reality. Specifically, we consider false positives (FPs), which are assumed true but are actually false, and false negatives (FNs), which are assumed false but are actually true. FPs may lead planners to action failures, while FNs may cause the agent to believe that deadends exist. We propose methods to detect and handle both types of inaccuracies, establish their theoretical properties, and evaluate their performance across a set of benchmark domains.","manuscriptTitle":"Contingent Planning in Domains with Unsafe Facts","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-15 16:06:48","doi":"10.21203/rs.3.rs-7536680/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8ec76756-a9b7-4be5-bb75-e11e9c05f6fe","owner":[],"postedDate":"September 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T11:02:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-15 16:06:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7536680","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7536680","identity":"rs-7536680","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}