Edited under the auspices of the Association of Logic, Language andInformation (FoLLI), this book constitutes the refereed proceedings ofthe 20th anniversary of the International Conference on LogicalAspects of Computational Linguistics, LACL 2016, held in LORIA Nancy,France, in December 2016. The 19 contributed papers, presentedtogether with 4 invited papers and 6 abstracts, were carefullyreviewed and selected from 38 submissions. The focus of the conferenceis the use of type theoretic, proof theoretic, and model theoreticmethods for describing and formalising natural language syntax,semantics, and pragmatics as well as the implementation of thecorresponding tools.

This book assesses the place of logic, mathematics, and computer science in present day, interdisciplinary areas of computational linguistics. Computational linguistics studies natural language in its various manifestations from a computational point of view, both on the theoretical level (modeling grammar modules dealing with natural language form and meaning and the relation between these two) and on the practical level (developing applications for language and speech technology). It is a collection of chapters presenting new and future research. The book focuses mainly on logical approaches to computational processing of natural language and on the applicability of methods and techniques from the study of formal languages, programming, and other specification languages. It presents work from other approaches to linguistics, as well, especially because they inspire new work and approaches.

This book focuses mainly on logical approaches to computational linguistics, but also discusses integrations with other approaches, presenting both classic and newly emerging theories and applications.Decades of research on theoretical work and practical applications have demonstrated that computational linguistics is a distinctively interdisciplinary area. There is convincing evidence that computational approaches to linguistics can benefit from research on the nature of human language, including from the perspective of its evolution. This book addresses various topics in computational theories of human language, covering grammar, syntax, and semantics. The common thread running through the research presented is the role of computer science, mathematical logic and other subjects of mathematics in computational linguistics and natural language processing (NLP). Promoting intelligent approaches to artificial intelligence (AI) and NLP, the book is intended for researchers and graduate students in the field.

This book investigates the phenomenon of actuality inferences, in which claims of ability are-in certain temporal contexts-interpreted as descriptions of actual events, instead of as descriptions of potentialities or possibilities. Although actuality inferences evidently arise in the interaction between modality and aspect, they have long resisted compositional explication in standard treatments of these semantic categories. Prerna Nadathur here pursues a new approach, in which actuality inferences are linked to a novel component in the semantics of ability: causal dependence relations. The account is developed through a comparative, crosslinguistic semantic analysis of three predicate classes that license similar inferences: implicative verbs in Finnish and English, enough/too predicates in French and English, and (modal) ability predicates in French, Hindi, and English. Similarities in the inferential profiles of these predicates are tied to their shared causal background structure, while their differences-including in sensitivity to grammatical aspect-derive from differences in asserted content and associated aspectual class contrasts. The central argument is that a complex causal structure for ability interacts with the compositional requirements of aspect to derive the observed actuality-ability ambiguity. The volume shows that causal structure and causal relationships shape patterns of linguistic inference beyond the overtly causal domain, and thus contributes to a new and growing body of research in which formal, computational causal models are employed as an analytic tool for lexical and compositional semantics.

This book covers theoretical work, applications, approaches, and techniques for computational models of information and its presentation by language (artificial, human, or natural in other ways). Computational and technological developments that incorporate natural language are proliferating. Adequate coverage encounters difficult problems related to ambiguities and dependency on context and agents (humans or computational systems). The goal is to promote computational systems of intelligent natural language processing and related models of computation, language, thought, mental states, reasoning, and other cognitive processes.

This book deals with applications of quantum mechanical techniques to areas outside of quantum mechanics, so-called quantum-like modeling. Research in this area has grown over the last 15 years. But even already more than 50 years ago, the interaction between Physics Nobelist Pauli and the psychologist Carl Jung in the 1950’s on seeking to find analogous uses of the complementarity principle from quantum mechanics in psychology needs noting. This book does NOT want to advance that society is quantum mechanical! The macroscopic world is manifestly not quantum mechanical. But this rules not out that one can use concepts and the mathematical apparatus from quantum physics in a macroscopic environment. A mainstay ingredient of quantum mechanics, is ‘quantum probability’ and this tool has been proven to be useful in the mathematical modelling of decision making. In the most basic experiment of quantum physics, the double slit experiment, it is known (from the works of A. Khrennikov) that the law of total probability is violated. It is now well documented that several decision making paradoxes in psychology and economics (such as the Ellsberg paradox) do exhibit this violation of the law of total probability. When data is collected with experiments which test ‘non-rational’ decision making behaviour, one can observe that such data often exhibits a complex non-commutative structure, which may be even more complex than if one considers the structure allied to the basic two slit experiment. The community exploring quantum-like models has tried to address how quantum probability can help in better explaining those paradoxes. Research has now been published in very high standing journals on resolving some of the paradoxes with the mathematics of quantum physics. The aim of this book is to collect the contributions of world’s leading experts in quantum like modeling in decision making, psychology, cognition, economics, and finance.

This book consists of contributions related to the definition, representation and parsing of MWEs. These reflect current trends in the representation and processing of MWEs. They cover various categories of MWEs such as verbal, adverbial and nominal MWEs, various linguistic frameworks (e.g. tree-based and unification-based grammars), various languages including English, French, Modern Greek, Hebrew, Norwegian), and various applications (namely MWE detection, parsing, automatic translation) using both symbolic and statistical approaches.