Vagueness and Aggregation in Multiple Sender Channels.
Vagueness is an extremely common feature of natural language, but does it actually play a positive, efficiency enhancing, role in communication? Adopting a probabilistic interpretation of vague terms, we propose that vagueness might act as a source of randomness when deciding what to assert. In this...
| Publicado en: | Erkenntnis Vol. 82; no. 5; pp. 1123 - 1161 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Oct2017
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=125871923&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 125871923 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 01650106 5KZ jtl: Erkenntnis issn: 01650106 maglogo: N pubinfo: dt: Oct2017 vid: 82 iid: 5 pid: 237 pub: Springer Nature artinfo: ui: 125871923 10.1007/s10670-016-9862-2 ppf: 1123 ppct: 38 formats: fmt: @attributes: type: P size: 1.2MB tig: atl: Vagueness and Aggregation in Multiple Sender Channels. aug: au: Lawry, Jonathan James, Oliver affil: Department of Engineering Mathematics , University of Bristol , Bristol BS8 1UB UK su: Vagueness (Philosophy) Natural languages Information theory Stochastic processes Boolean functions sug: subj: Vagueness (Philosophy) Natural languages Information theory Stochastic processes Boolean functions ab: Vagueness is an extremely common feature of natural language, but does it actually play a positive, efficiency enhancing, role in communication? Adopting a probabilistic interpretation of vague terms, we propose that vagueness might act as a source of randomness when deciding what to assert. In this context we investigate the efficacy of multiple sender channels in which senders choose assertions stochastically according to vague definitions of the relevant words, and a receiver then aggregates the different signals. These vague channels are then compared with Boolean channels in which assertions are selected deterministically based on classical (crisp) definitions. We show that given a sufficient number of senders, a linear stochastic channel outperforms Boolean channels when performance is measured by the expected squared error between the actual value described by the senders and the receiver's estimate of it based on the signals they receive. The number of senders required for vague channels to be at least as accurate as Boolean channels is shown to be a decreasing function of the size of the language i.e. the number of description labels available to the senders. Vague channels are then shown to be robust to transmission error provided the error rate is not too large. In addition, we investigate the behaviour of both Boolean and vague channels for a parametrised family of distributions on the input values. Finally, we consider optimal vague channels assuming a fixed number of senders and show that, provided there are more than two senders, a vague channel can be found that outperforms the optimal Boolean channel. In this context, we show that for channels with relatively low numbers of senders S-curve production functions are optimal. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Erkenntnis is a copyright of Springer, 2017. All Rights Reserved. item: Erkenntnis holder: Springer Nature dt: @attributes: year: 2017 holdings: @attributes: islocal: N |
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