At the Intersection of Language, Logic, and Information : ESSLLI 2018 Student Session, Sofia, Bulgaria, August 6-17, 2018, Selected Papers (Theoretical Computer Science and General Issues)

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At the Intersection of Language, Logic, and Information : ESSLLI 2018 Student Session, Sofia, Bulgaria, August 6-17, 2018, Selected Papers (Theoretical Computer Science and General Issues)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 225 p.
  • 言語 ENG
  • 商品コード 9783662596197

Full Description

​The European Summer School in Logic, Language and Information (ESSLLI) is organized every year by the Association for Logic, Language and Information (FoLLI) in different sites around Europe. The papers cover vastly dierent topics, but each fall in the intersection of the three primary topics of ESSLLI: Logic, Language and Computation. The 14 papers presented in this volume have been selected among 24 papers presented by talks or posters at the Student Sessions of the 30th edition of ESSLLI, held in 2018 in Sofia, Bulgaria.The Student Session is a forum for PhD and Master students to present their research at the interfaces of logic, language and computation. It features three tracks: Logic and Computation (LoCo), Logic and Language (LoLa), and Language and Computation (LaCo).

Contents

Simulating the No Alternatives Argument in a Social Setting.- Readings of Plurals and Common Ground.- Towards an analysis of the agent-oriented manner verb sorgfältig ('carefully').-  Social Choice and the Problem of Recommending Essential Readings.- Towards a 2-Multiple Context-Free Grammar for the 3-dimensional  Dyck Language.- Compositionality in Privative Adjectives: Extending Dual Content Semantics.-  Definiteness with Bare Nouns in Shan.-  The challenge of metafictional anaphora.- Rule-based reasoners in epistemic logic.- Free Relatives, Feature Recycling, and Reprojection in Minimalist Grammars.- Playing with Information Source.- Disjunction under Deontic Modals: Experimental Data.- "First Things First": an Inquisitive Plausability-Urgency Model.- Interpreting Intensifiers for Relative Adjectives: Comparing Models and Theories.  

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