English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Logics with analogous semantics, such as Fuzzy Logic, have a number ofexplanatory and application advantages, the most well-known being the abilityto help experts develop control systems. From a cognitive systems perspective,such languages also have the advantage of being grounded in perception. Forsocial decision making in humans, it is vital that logical conclusions aboutothers (cognitive empathy) are grounded in empathic emotion (affectiveempathy). Classical Fuzzy Logic, however, has several disadvantages: it is notobvious how complex formulae, e.g., the description of events in a text, can be(a) formed, (b) grounded, and (c) used in logical reasoning. The two-layeredContext Logic (CL) was designed to address these issue. Formally based on alattice semantics, like classical Fuzzy Logic, CL also features an analogoussemantics for complex fomulae. With the Activation Bit Vector Machine (ABVM),it has a simple and classical logical reasoning mechanism with an inherentimagery process based on the Vector Symbolic Architecture (VSA) model ofdistributed neuronal processing. This paper adds to the existing theory howscales, as necessary for adjective and verb semantics can be handled by thesystem.

Scales and Hedges in a Logic with Analogous Semantics