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Autolexical Grammar (AG) explains both the coherent systematicity and the pervasive idiosyncrasies present in natural language through a unified, multimodular approach moderated by lexical constraints. This chapter presents recent research in cognitive neuroscience that bears on the representational strengths of AG. While AG does not strive to be a psycholinguistic model of cognitive processing in real time, the ability of AG to represent mismatch and resolution as formal constraints, and the emphasis that AG places on the lexicon as the moderating factor in constraint satisfaction, provides descriptive mechanisms that can further illuminate cognitive approaches to language processing.

Autolexical theory (Linguistics). --- Grammar, Comparative and general --- Hierarchy (Linguistics). --- Pragmatics. --- Syntax. --- Autolexical theory (Linguistics) --- Hierarchy (Linguistics) --- Stratification (Linguistics) --- Hierarchies --- Linguistic analysis (Linguistics) --- Linguistics --- Compositionality (Linguistics) --- Generative grammar --- Language and languages --- Syntax --- Pragmalinguistics --- General semantics --- Logic, Symbolic and mathematical --- Semantics (Philosophy) --- Philosophy --- Philology --- Grammar, Comparative and general Syntax

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The year's finest mathematics writing from around the worldThis annual anthology brings together the year's finest mathematics writing from around the world. Featuring promising new voices alongside some of the foremost names in the field, The Best Writing on Mathematics 2016 makes available to a wide audience many articles not easily found anywhere else-and you don't need to be a mathematician to enjoy them. These writings offer surprising insights into the nature, meaning, and practice of mathematics today. They delve into the history, philosophy, teaching, and everyday occurrences of math, and take readers behind the scenes of today's hottest mathematical debates.Here Burkard Polster shows how to invent your own variants of the Spot It! card game, Steven Strogatz presents young Albert Einstein's proof of the Pythagorean Theorem, Joseph Dauben and Marjorie Senechal find a treasure trove of math in New York's Metropolitan Museum of Art, and Andrew Gelman explains why much scientific research based on statistical testing is spurious. In other essays, Brian Greene discusses the evolving assumptions of the physicists who developed the mathematical underpinnings of string theory, Jorge Almeida examines the misperceptions of people who attempt to predict lottery results, and Ian Stewart offers advice to authors who aspire to write successful math books for general readers. And there's much, much more.In addition to presenting the year's most memorable writings on mathematics, this must-have anthology includes a bibliography of other notable writings and an introduction by the editor, Mircea Pitici. This book belongs on the shelf of anyone interested in where math has taken us-and where it is headed.

Mathematics. --- Math --- Science