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New scientific paradigms typically consist of an expansion of the conceptual language with which we describe the world. Over the past decade, theoretical physics and quantum information theory have turned to category theory to model and reason about quantum protocols. This new use of categorical and algebraic tools allows a more conceptual and insightful expression of elementary events such as measurements, teleportation and entanglement operations, that were obscured in previous formalisms. Recent work in natural language semantics has begun to use these categorical methods to relate grammatical analysis and semantic representations in a unified framework for analysing language meaning, and...
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Doing Philosophy provides a practical guide to studying philosophy for undergraduate students. The book presents strategies for developing the necessary skills that will allow students to get the most out of this fascinating subject. It examines what it means to think, read, discuss and write philosophically, giving advice on: Reading and analysing philosophical texts Preparing for and participating in seminars Choosing essay topics Constructing arguments and avoiding plagiarism Using libraries, the internet and other resources Technical terms, forms of expression and logical notation The second edition is fully revised and expanded throughout, packed with practical exercises, useful examples and fully up-to-date resources. It also features for the first time a full companion website with additional resources and a range of pedagogical tools and activities designed for students and lecturers to use both in the classroom and in seminar preparation. Concise and accessible, Doing Philosophy equips the student with the tools needed to successfully engage in discussing, reading and writing philosophy.
These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: exploiting subprograms in genetic programming, schema frequencies in GP, Accessible AI, GP for Big Data, lexicase selection, symbolic regression techniques, co-evolution of GP and LCS, and applying ecological principles to GP. It also covers several chapters on best practices and lessons learned from hands-on experience. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
This book presents interdisciplinary research in the science of Human Cognition through mathematical and computational modeling and simulation. Featuring new approaches developed by leading experts in the field of cognitive science, it highlights the relevance and depth of this important area of social sciences and its expanding reach into the biological, physical, computational and mathematical sciences. This contributed volume compiles the most recent advancements and cutting-edge applications of cognitive modeling, employing a genuinely multidisciplinary approach to simulate thinking, memory, and decision-making. The topics covered encompass a wide range of subjects, such as Agent-based M...
This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective "deep" comes from the fact that the distribution is parameterized using deep neural networks. There are two di...
This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read at Oxford Academic and offered as a free PDF download from OUP and selected open access locations. This book introduces a systematic framework for understanding and investigating lexical variation, using a distributional semantics approach. Distributional semantics embodies the idea that the context in which a word occurs reveals the meaning of that word. In contemporary corpus linguistics, that idea takes shape in various types of quantitative analysis of the corpus contexts in which words appear. In this book, the authors explore how count-based token-level semantic vector ...
This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.
This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Symposium on Quantum Interaction, QI 2011, held in Aberdeen, UK, in June 2011. The 26 revised full papers and 6 revised poster papers, presented together with 1 tutorial and 1 invited talk were carefully reviewed and selected from numerous submissions during two rounds of reviewing and improvement. The papers show the cross-disciplinary nature of quantum interaction covering topics such as computation, cognition, mechanics, social interaction, semantic space and information representation and retrieval.