Graded Modality
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Graded Modality
Author: Daniel Lassiter
language: en
Publisher: Oxford University Press
Release Date: 2017-05-19
This book explores graded expressions of modality, a rich and underexplored source of insight into modal semantics. Studies on modal language to date have largely focussed on a small and non-representative subset of expressions, namely modal auxiliaries such as must, might, and ought. Here, Daniel Lassiter argues that we should expand the conversation to include gradable modals such as more likely than, quite possible, and very good. He provides an introduction to qualitative and degree semantics for graded meaning, using the Representational Theory of Measurement to expose the complementarity between these apparently opposed perspectives on gradation. The volume explores and expands the typology of scales among English adjectives and uses the result to shed light on the meanings of a variety of epistemic and deontic modals. It also demonstrates that modality is deeply intertwined with probability and expected value, connecting modal semantics with the cognitive science of uncertainty and choice.
Modality, Semantics and Interpretations
This contributed volume includes both theoretical research on philosophical logic and its applications in artificial intelligence, mostly employing the concepts and techniques of modal logic. It collects selected papers presented at the Second Asia Workshop on Philosophical Logic, held in Guangzhou, China in 2014, as well as a number of invited papers by specialists in related fields. The contributions represent pioneering philosophical logic research in Asia.
Proof Theory of Modal Logic
Author: Heinrich Wansing
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-06-29
Proof Theory of Modal Logic is devoted to a thorough study of proof systems for modal logics, that is, logics of necessity, possibility, knowledge, belief, time, computations etc. It contains many new technical results and presentations of novel proof procedures. The volume is of immense importance for the interdisciplinary fields of logic, knowledge representation, and automated deduction.
