Concepts in Action: Representation, Learning, and Application, Bechberger Lucas, Kьhnberger Kai-Uwe, Liu Mingya

Автор: Borg Emma, Picciotto S Sol, Lorange Peter,
Название: Meaning and Representation
ISBN: 0631235779 ISBN-13(EAN): 9780631235774
Издательство: Wiley
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Цена: 19120.00 T
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Описание: * Discusses the relationship between meaning and representation. * Illustrates the differences that exist on the question of how formal representations relate to semantic representations. * Includes contributions by Tim Crane, Jerry Fodor, Paul Horwich, John Hyman, Ernie Lepore, Gregory McCulloch and Mark Sainsbury.

Автор: Dov M. Gabbay; Philippe Smets
Название: Quantified Representation of Uncertainty and Imprecision
ISBN: 9048150388 ISBN-13(EAN): 9789048150380
Издательство: Springer
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Цена: 277650.00 T
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Описание: This Handbook was produced in the style of previous handbook series like the Handbook of Philosoph- ical Logic, the Handbook of Logic in Computer Science, the Handbook of Logic in Artificial Intelligence and Logic Programming, and can be seen as a companion to them in covering the wide applications of logic and reasoning.

Автор: E. Marbach
Название: Mental Representation and Consciousness
ISBN: 9048142342 ISBN-13(EAN): 9789048142347
Издательство: Springer
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Цена: 65170.00 T
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Описание: conditions of the possibility of Experience ... The essence of Experience that phenomenological analysis of Experience elucidates is the same as the possibility of Experience, and all that which is determined in the essence, in the possibility of Experience, is eo ipso 1 condition of the possibility of Experience.

Автор: E. Cornell Way
Название: Knowledge Representation and Metaphor
ISBN: 904814079X ISBN-13(EAN): 9789048140794
Издательство: Springer
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Цена: 181630.00 T
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Описание: This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data- processing systems of all kinds, no matter whether human, (other) animal, or machine.

Автор: Alexander Riegler; Markus Peschl; Astrid von Stein
Название: Understanding Representation in the Cognitive Sciences
ISBN: 1475772459 ISBN-13(EAN): 9781475772456
Издательство: Springer
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Цена: 139750.00 T
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Описание: urrently a paradigm shift is occurring in for the conventional understanding of represen- which the traditional view of the brain as tions. The paper also summarizes the rationale for C representing the things of the world is the selection of contributions to this volume, which challenged in several respects. The present volume will roughly proceed from relatively realist c- is placed at the edge of this transition. Based on the ceptions of representation to more constructivist 1997 conference New Trends in Cognitive Sci- interpretations. The final chapter of discussions, ence in Vienna, Austria, it tries to collect and in- taped during and at the end of the conference, p- grate evidence from various disciplines such as p- vides the reader with the possibility to reflect upon losophy of science, neuroscience, computational the different approaches and thus contributes to b- approaches, psychology, semiotics, evolutionary ter and more integrative understanding of their biology, social psychology etc., to foster a new thoughts and ideas. understanding of representation. The subjective experience of an outside world This book has a truly interdisciplinary character. It seems to suggest a mapping process where environ- is presented in a form that is readily accessible to mental entities are projected into our mind via some professionals and students alike across the cognitive kind of transmission. While a profound critique of sciences such as neuroscience, computer science, this idea is nearly as old as philosophy, it has gained philosophy, psychology, and sociology.

Автор: Bechberger Lucas, Kьhnberger Kai-Uwe, Liu Mingya
Название: Concepts in Action: Representation, Learning, and Application
ISBN: 303069822X ISBN-13(EAN): 9783030698225
Издательство: Springer
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Цена: 37260.00 T
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Описание: This open access book is a timely contribution in presenting recent issues, approaches, and results that are not only central to the highly interdisciplinary field of concept research but also particularly important to newly emergent paradigms and challenges.

Автор: Hamilton William L.
Название: Graph Representation Learning
ISBN: 1681739631 ISBN-13(EAN): 9781681739632
Издательство: Mare Nostrum (Eurospan)
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Цена: 57290.00 T
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Описание: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis.

This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs-a nascent but quickly growing subset of graph representation learning.

Автор: Gem Stapleton; John Howse; John Lee
Название: Diagrammatic Representation and Inference
ISBN: 3540877290 ISBN-13(EAN): 9783540877295
Издательство: Springer
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Описание: Constitutes the proceedings of the 5th International Conference on Theory and Application of Diagrams, Diagrams 2008, held in Herrsching, Germany, in September 2008. This book organizes the papers in topical sections on diagram aesthetics and layout, psychological and cognitive issues, applications of diagrams, and theoretical aspects.

Автор: Juan A. Fern?ndez; Javier Gonz?lez
Название: Multi-Hierarchical Representation of Large-Scale Space
ISBN: 9048158613 ISBN-13(EAN): 9789048158614
Издательство: Springer
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Цена: 130590.00 T
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Описание: It has been stated in psychology that human brain arranges information in a way that improves efficiency in performing common tasks, for example, information about our spatial environment is conveniently structured for efficient route finding.

Автор: D.A. Anapolitanos
Название: Leibniz: Representation, Continuity and the Spatiotemporal
ISBN: 9048151384 ISBN-13(EAN): 9789048151387
Издательство: Springer
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Цена: 139750.00 T
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Описание: Anapolitanos critically examines and evaluates three basic characteristics of the Leibnizian metaphysical system: Leibniz`s version of representation; Chapter II examines the principle of continuity, including continuity as a general feature of every level of Leibniz`s metaphysics.

Автор: Ellen Hisdal
Название: Logical Structures for Representation of Knowledge and Uncertainty
ISBN: 3790824585 ISBN-13(EAN): 9783790824582
Издательство: Springer
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Цена: 153720.00 T
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Описание: The M logic goes an important step further than the BP logic in that it can distinguish between certain types of information supply sentences which have the same representation in the BP logic as well as in traditional first order logic, although they clearly have different meanings (see example 6.

Автор: Eugene Fink
Название: Changes of Problem Representation
ISBN: 3790825182 ISBN-13(EAN): 9783790825183
Издательство: Springer
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Цена: 153720.00 T
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Описание: The purpose of our research is to enhance the efficiency of AI problem solvers by automating representation changes. We have developed a system that improves the description of input problems and selects an appropriate search algorithm for each given problem.