This volume presents articles that focus on the application of formal models in the study of language in a variety of innovative ways, and is dedicated to Jacques Moeschler, professor at University of Geneva, to mark the occasion of his 60th birthday. The contributions, by seasoned and budding linguists of all different linguistic backgrounds, reflect Jacques Moeschler’s diverse and visionary research over the years. The book contains three parts. The first part shows how different formal models can be applied to the analysis of such diverse problems as the syntax, semantics and pragmatics of tense, aspect and deictic expressions, syntax and pragmatics of quantifiers and semantics and pragmatics of connectives and negation. The second part presents the application of formal models to the treatment of cognitive issues related to the use of language, and in particular, demonstrating cognitive accounts of different types of human interactions, the context in utterance interpretation (salience, inferential comprehension processes), figurative uses of language (irony pretence), the role of syntax in Theory of Mind in autism and the analysis of the aesthetics of nature. Finally, the third part addresses computational and corpus-based approaches to natural language for investigating language variation, language universals and discourse related issues. This volume will be of great interest to syntacticians, pragmaticians, computer scientists, semanticians and psycholinguists.

A formal model in the social sciences builds explanations when it structures the reasoning underlying a theoretical argument, opens venues for controlled experimentation, and can lead to hypotheses. Yet more importantly, models evaluate theory, build theory, and enhance conjectures. Formal Modeling in Social Science addresses the varied helpful roles of formal models and goes further to take up more fundamental considerations of epistemology and methodology. The authors integrate the exposition of the epistemology and the methodology of modeling and argue that these two reinforce each other. They illustrate the process of designing an original model suited to the puzzle at hand, using multiple methods in diverse substantive areas of inquiry. The authors also emphasize the crucial, though underappreciated, role of a narrative in the progression from theory to model. Transparency of assumptions and steps in a model means that any analyst will reach equivalent predictions whenever she replicates the argument. Hence, models enable theoretical replication, essential in the accumulation of knowledge. Formal Modeling in Social Science speaks to scholars in different career stages and disciplines and with varying expertise in modeling.

Ever since Chomsky laid the framework for a mathematically formal theory of syntax, two classes of formal models have held wide appeal. The finite state model offered simplicity. At the opposite extreme numerous very powerful models, most notable transformational grammar, offered generality. As soon as this mathematical framework was laid, devastating arguments were given by Chomsky and others indicating that the finite state model was woefully inadequate for the syntax of natural language. In response, the completely general transformational grammar model was advanced as a suitable vehicle for capturing the description of natural language syntax. While transformational grammar seems likely to be adequate to the task, many researchers have advanced the argument that it is "too adequate. " A now classic result of Peters and Ritchie shows that the model of transformational grammar given in Chomsky's Aspects [IJ is powerful indeed. So powerful as to allow it to describe any recursively enumerable set. In other words it can describe the syntax of any language that is describable by any algorithmic process whatsoever. This situation led many researchers to reasses the claim that natural languages are included in the class of transformational grammar languages. The conclu sion that many reached is that the claim is void of content, since, in their view, it says little more than that natural language syntax is doable algo rithmically and, in the framework of modern linguistics, psychology or neuroscience, that is axiomatic.

This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson's ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth) .

This volume is a collection of papers written by several researchers that have in common the use of bio-inspired models to approach formal and natural languages. The main goal of the volume is to promote interdisciplinarity among linguistics, biology and computation. The area of convergence between these three disciplines is giving rise to the emergence of new scientific paradigms that will have an epistemological, social and cultural impact. The book is organized around three thematic areas. Every area relates two of the three main topics: language, computation and biology. This volume stands out from existing publications because of its interdisciplinary nature. There has been a long tradition of interchanging methods among the aforementioned three disciplines, but it is difficult to find a single volume where this interchange of methods is shown. The volume includes chapters that clearly illustrate these interdisciplinary approaches and their benefits. This book will be of value to specialists who work in linguistics, biology or computation, and have interest in using methods from other disciplines that can provide new ideas, new tools and new formalisms to approach their problems, and that can help in the improvement of their theories and models.

A collection of articles by leading experts in theoretical computer science, this volume commemorates the 75th birthday of Professor Rani Siromoney, one of the pioneers in the field in India. The articles span the vast range of areas that Professor Siromoney has worked in or influenced, including grammar systems, picture languages and new models of computation.