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text Lasersohn, Peter N. Lasersohn, Peter N. McCarthy, Timothy G. Livengood, Jonathan M. Levinstein, Benjamin A Lee, Steven Fong-Yi 2020-03-02T21:58:22Z 2020-03-02T21:58:22Z 2019-12-06 2019-12 In this dissertation I argue that truth-conditional semantics for vague predicates, combined with a Bayesian account of statistical inference incorporating knowledge of truth-conditions of utterances, generates false predictions regarding negations and metalinguistic inference. I thus propose a fundamentally probabilistic semantics for vagueness on which the meaning of a vague predicate is a likelihood function on the states it encodes, with these likelihoods being generated via reinforcement learning in a signaling game. Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-02-28 without embargo terms The student, Steven Lee, accepted the attached license on 2019-12-04 at 13:52. The student, Steven Lee, submitted this Dissertation for approval on 2019-12-04 at 17:27. This Dissertation was approved for publication on 2019-12-06 at 09:49. DSpace SAF Submission Ingestion Package generated from Vireo submission #14693 on 2020-02-28 at 17:15:07 Made available in DSpace on 2020-03-02T21:58:22Z (GMT). No. of bitstreams: 3 LEE-DISSERTATION-2019.pdf: 4568264 bytes, checksum: 05e511cfc22ba094a56b484903a8fdbc (MD5) LICENSE.txt: 4207 bytes, checksum: 85622553d29935d292b6b2b2ec97ca7f (MD5) PROQUEST_LICENSE.txt: 4553 bytes, checksum: acca5d78f6e06a7e4ab33fd498d29e12 (MD5) Previous issue date: 2019-12-06 application/pdf http://hdl.handle.net/2142/106242 en Copyright 2019 Steven Fong-yi Lee semantics pragmatics vagueness probability game theory artificial intelligence reinforcement learning Bayes Bayesian linguistics philosophy statistical inference cognitive science Grice formal semantics Montague Sorites logic dynamic semantics truth-conditions Probabilistic semantics for vagueness text Philosophy Philosophy University of Illinois at Urbana-Champaign Dissertation Ph.D.