{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T16:57:06Z","timestamp":1772729826822,"version":"3.50.1"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T00:00:00Z","timestamp":1702512000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T00:00:00Z","timestamp":1702512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p><jats:italic>Goal Recognition<\/jats:italic>is the task of discerning the intended goal that an agent aims to achieve, given a set of goal hypotheses, a domain model, and a sequence of observations (i.e., a sample of the plan executed in the environment). Existing approaches assume that goal hypotheses comprise a single conjunctive formula over a single final state and that the environment dynamics are deterministic, preventing the recognition of temporally extended goals in more complex settings. In this paper, we expand goal recognition to<jats:italic>temporally extended goals<\/jats:italic>in<jats:italic>Fully Observable Non-Deterministic<\/jats:italic>(<jats:sc>fond<\/jats:sc>) planning domain models, focusing on goals on finite traces expressed in<jats:italic>Linear Temporal Logic<\/jats:italic>(<jats:sc>ltl<\/jats:sc><jats:inline-formula><jats:alternatives><jats:tex-math>$$_f$$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:msub><mml:mrow\/><mml:mi>f<\/mml:mi><\/mml:msub><\/mml:math><\/jats:alternatives><\/jats:inline-formula>) and<jats:italic>Pure-Past Linear Temporal Logic<\/jats:italic>(<jats:sc>ppltl<\/jats:sc>). We develop the first approach capable of recognizing goals in such settings and evaluate it using different<jats:sc>ltl<\/jats:sc><jats:inline-formula><jats:alternatives><jats:tex-math>$$_f$$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:msub><mml:mrow\/><mml:mi>f<\/mml:mi><\/mml:msub><\/mml:math><\/jats:alternatives><\/jats:inline-formula>and<jats:sc>ppltl<\/jats:sc>goals over six<jats:sc>fond<\/jats:sc>planning domain models. Empirical results show that our approach is accurate in recognizing temporally extended goals in different recognition settings.<\/jats:p>","DOI":"10.1007\/s10489-023-05087-1","type":"journal-article","created":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T10:01:45Z","timestamp":1702548105000},"page":"470-489","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Temporally extended goal recognition in fully observable non-deterministic domain models"],"prefix":"10.1007","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3600-3348","authenticated-orcid":false,"given":"Ramon Fraga","family":"Pereira","sequence":"first","affiliation":[]},{"given":"Francesco","family":"Fuggitti","sequence":"additional","affiliation":[]},{"given":"Felipe","family":"Meneguzzi","sequence":"additional","affiliation":[]},{"given":"Giuseppe","family":"De Giacomo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,12,14]]},"reference":[{"key":"5087_CR1","doi-asserted-by":"crossref","unstructured":"Aineto D, Jimenez S, Onaindia E (2021) Generalized temporal inference via planning. 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