Pregled bibliografske jedinice broj: 874779
Formalizing Inferential Evidentiality: From Justification Logic to Machine Learning
Formalizing Inferential Evidentiality: From Justification Logic to Machine Learning // Formal Methods and Science in Philosophy
Dubrovnik, Hrvatska, 2017. str. 1-1 (predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 874779 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Formalizing Inferential Evidentiality: From
Justification Logic to Machine Learning
Autori
Šekrst, Kristina
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Skup
Formal Methods and Science in Philosophy
Mjesto i datum
Dubrovnik, Hrvatska, 04.05.2017. - 06.05.2017
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
justification logic, logic of proofs, evidentiality, machine learning
Sažetak
Evidentiality is a grammatical category in which the speaker is obligated to state the evidence for his statement, otherwise the statement is ungrammatical. One can use justification logic – that unfolds modalities into justification terms – to formalize inferential rules in such languages. It will be shown how justification logic can be used to formalize indirect evidentiality, that lie on speaker’s background knowledge or inference, unlike direct evidentials that depend on sensory perception. Hence, it will be shown how justification logic axiomatization of such examples can be used in theoretical computer science, where such abstract notions can be processed in machine learning of rules and concepts in natural language.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Računarstvo, Filozofija
POVEZANOST RADA
Projekti:
IP-2014-09-9378 - Logika, pojmovi i komunikacija (LogiCCom) (Kovač, Srećko, HRZZ - 2014-09) ( CroRIS)
Ustanove:
Institut za filozofiju, Zagreb
Profili:
Kristina Šekrst
(autor)
