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Linguistics for the Age of AI
A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.
Agents in the Long Game of AI
A novel approach to hybrid AI aimed at developing trustworthy agent collaborators. The vast majority of current AI relies wholly on machine learning (ML). However, the past thirty years of effort in this paradigm have shown that, despite the many things that ML can achieve, it is not an all-purpose solution to building human-like intelligent systems. One hope for overcoming this limitation is hybrid AI: that is, AI that combines ML with knowledge-based processing. In Agents in the Long Game of AI, Marjorie McShane, Sergei Nirenburg, and Jesse English present recent advances in hybrid AI with special emphases on content-centric computational cognitive modeling, explainability, and development...
Language Engineering for Lesser-studied Languages
"Technologies enabling computers to process specific languages facilitate economic and political progress of societies where these languages are spoken. Development of methods and systems for language processing is therefore a worthy goal for national governments as well as for business entities and scientific and educational institutions in every country in the world. As work on systems and resources for the 'lower-density' languages becomes more widespread, an important question is how to leverage the results and experience accumulated by the field of computational linguistics for the major languages in the development of resources and systems for lower-density languages. This issue has be...
A Theory of Ellipsis
Ellipsis is the non-expression of one or more sentence elements whose meaning can be reconstructed either from the context or from a person's knowledge of the world. In speech and writing, ellipsis is pervasive, contributing in various ways to the economy, speed, and style of communication. Resolving ellipsis is a particularly challenging issue in natural language processing, since not only must meaning be gleaned from missing elements but the fact that something meaningful is missing must be detected in the first place. Marjorie McShane presents a comprehensive theory of ellipsis that supports the formal, cross-linguistic description of elliptical phenomena taking into account the various f...
Ontology and the Lexicon
An edited collection focusing on the technology involved in enabling integration between lexical resources and semantic technologies.
New Trends of Research in Ontologies and Lexical Resources
In order to exchange knowledge, humans need to share a common lexicon of words as well as to access the world models underlying that lexicon. What is a natural process for a human turns out to be an extremely hard task for a machine: computers can’t represent knowledge as effectively as humans do, which hampers, for example, meaning disambiguation and communication. Applied ontologies and NLP have been developed to face these challenges. Integrating ontologies with (possibly multilingual) lexical resources is an essential requirement to make human language understandable by machines, and also to enable interoperability and computability across information systems and, ultimately, in the We...
The Cambridge Handbook of Computational Cognitive Sciences
The Cambridge Handbook of Computational Cognitive Sciences is a comprehensive reference for this rapidly developing and highly interdisciplinary field. Written with both newcomers and experts in mind, it provides an accessible introduction of paradigms, methodologies, approaches, and models, with ample detail and illustrated by examples. It should appeal to researchers and students working within the computational cognitive sciences, as well as those working in adjacent fields including philosophy, psychology, linguistics, anthropology, education, neuroscience, artificial intelligence, computer science, and more.
Biologically Inspired Cognitive Architectures 2010
"This book presents the proceedings of the First International Conference on Biologically Inspired Cognitive Architectures (BICA 2010), which is also the First Annual Meeting of the BICA Society. A cognitive architecture is a computational framework for the design of intelligent, even conscious, agents. It may draw inspiration from many sources, such as pure mathematics, physics or abstract theories of cognition. A biologically inspired cognitive architecture (BICA) is one which incorporates formal mechanisms from computational models of human and animal cognition, which currently provide the only physical examples with the robustness, flexibility, scalability and consciousness that artifici...
Parametric Variation
Parametric variation in linguistic theory refers to the systematic grammatical variation permitted by the human language faculty. This book is a defence of the parametric approach to linguistic variation, set within the framework of the Minimalist Program.
