Search Results for abductive-reasoning-and-learning

This book contains leading survey papers on the various aspects of Abduction, both logical and numerical approaches.

Author: Dov M. Gabbay

Publisher: Springer Science & Business Media

ISBN: 9789401717335

Category: Mathematics

Page: 442

View: 455

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This book contains leading survey papers on the various aspects of Abduction, both logical and numerical approaches. Abduction is central to all areas of applied reasoning, including artificial intelligence, philosophy of science, machine learning, data mining and decision theory, as well as logic itself.
2013-04-17 By Dov M. Gabbay

Learning through abductive reasoning is as pervasive as it is important for generating, expanding, and justifying many of our knowledge claims. And yet, abductive reasoning, and the learning on which it depends, is not widely known.

Author: Norbert M. Seel

Publisher: Springer Science & Business Media

ISBN: 9781441914279

Category: Education

Page: 3536

View: 471

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Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.
2011-10-05 By Norbert M. Seel

Author:

Publisher:

ISBN: OCLC:59277618

Category: Computer software

Page: 11

View: 951

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3. Abductive inference constitutes one of the main organizational sources of coherent actions emergent from self-organizing learning processes. Hypotheses 1–3 are investigated in two steps: Section 2, Abductive Reasoning and the Debate ...

Author: Lorenzo Magnani

Publisher: Springer

ISBN: 9783540719861

Category: Technology & Engineering

Page: 525

View: 418

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The volume is based on papers presented at the international conference on Model-Based Reasoning in Science and Medicine held in China in 2006. The presentations explore how scientific thinking uses models and explanatory reasoning to produce creative changes in theories and concepts. The contributions to the book are written by researchers active in the area of creative reasoning in science and technology. They include the subject area’s most recent results and achievements.
2007-06-30 By Lorenzo Magnani

So, inductive machine learning architecture took on the lead with the abduction reasoning process being cast to the background. Slowly but surely emerging out of the main trends, decisive attention was once again given to abduction.

Author: Jean-Guy Meunier

Publisher: Bloomsbury Publishing

ISBN: 9781350166639

Category: Literary Criticism

Page: 288

View: 556

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Can semiotics and computers be compatible? Can computation advance semiotics by enhancing the scientific basis of the theory of signs? Coupling semiotics, a philosophical and phenomenological tradition concerned with theories of signs, with computation, a formal discipline, may seem controversial and paradoxical. Computational Semiotics tackles these controversies head-on and attempts to bridge this gap. Showing how semiotics can build the same type of conceptual, formal, and computational models as other scientific projects, this book opens up a rich domain of inquiry toward the formal understanding of semiotic artifacts and processes. Examining how pairing semiotics with computation can bring more methodological rigor and logical consistency to the epistemic quest for the forms and functions of meaning, without compromising the important interpretive dynamics of semiotics, this book offers a new cutting-edge, model-driven theory to the field.
2021-08-12 By Jean-Guy Meunier

According to Reid, Jason used abductive reasoning to arrive at the general rule (1) [The number of handshakes is] the number [of people] times half the number, subtract half the number. (Reid, 2003, p. 6) From the specific case: Because ...

Author: Adalira Sáenz-Ludlow

Publisher: Springer

ISBN: 9789463003377

Category: Education

Page: 232

View: 784

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Semiotics as a Tool for Learning Mathematics is a collection of ten theoretical and empirical chapters, from researchers all over the world, who are interested in semiotic notions and their practical uses in mathematics classrooms. Collectively, they present a semiotic contribution to enhance pedagogical aspects both for the teaching of school mathematics and for the preparation of pre-service teachers. This enhancement involves the use of diagrams to visualize implicit or explicit mathematical relations and the use of mathematical discourse to facilitate the emergence of inferential reasoning in the process of argumentation. It will also facilitate the construction of proofs and solutions of mathematical problems as well as the progressive construction of mathematical conceptions that, eventually, will approximate the concept(s) encoded in mathematical symbols. These symbols hinge not only of mental operations but also on indexical and iconic aspects; aspects which often are not taken into account when working on the meaning of mathematical symbols. For such an enhancement to happen, it is necessary to transform basic notions of semiotic theories to make them usable for mathematics education. In addition, it is also necessary to back theoretical claims with empirical data. This anthology attempts to deal with such a conjunction. Overall, this book can be used as a theoretical basis for further semiotic considerations as well as for the design of different ways of teaching mathematical concepts.
2015-12-17 By Adalira Sáenz-Ludlow

10.1.2 Learning as an evidential reasoning task In this section we explore learning as an evidential reasoning task. Given a task, a prior belief or bias, and some data, the learning task is to produce an updated theory of the data (the ...

Author: P.A. Flach

Publisher: Springer Science & Business Media

ISBN: 9789401706063

Category: Mathematics

Page: 309

View: 458

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From the very beginning of their investigation of human reasoning, philosophers have identified two other forms of reasoning, besides deduction, which we now call abduction and induction. Deduction is now fairly well understood, but abduction and induction have eluded a similar level of understanding. The papers collected here address the relationship between abduction and induction and their possible integration. The approach is sometimes philosophical, sometimes that of pure logic, and some papers adopt the more task-oriented approach of AI. The book will command the attention of philosophers, logicians, AI researchers and computer scientists in general.
2013-04-18 By P.A. Flach

... learning call for both inductive reasoning, drawing inferences from specific observations to create overarching abstract principles that guide insight and action; and abductive reasoning, generating and testing the best possible ...

Author: Carmela R. Nanton

Publisher: John Wiley & Sons

ISBN: 9781119248156

Category: Education

Page: 112

View: 987

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Much like how tectonic plates interact, this volume explores the convergent, divergent, and transforming interaction of multiple forces pressing against adult contemporary education. Presenting multiple perspectives and environments, topics covered include: possibilities and requirements for change that will be needed in curriculum, philosophy, programs and practice, strategies for negotiating the interactive boundaries of a dynamic, complex, fluid global environment, and case studies and examples from theory, pedagogy, technology, healthcare, workplace, society, and policies. This is the 149th volume of the Jossey Bass series New Directions for Adult and Continuing Education. Noted for its depth of coverage, it explores issues of common interest to instructors, administrators, counselors, and policymakers in a broad range of education settings, such as colleges and universities, extension programs, businesses, libraries, and museums.
2016-02-22 By Carmela R. Nanton

A series of recent studies in economics and business administration have revealed that abductive reasoning is acquired through learning by doing or by accumulating aesthetic perceptions nurtured by professional experiences (von Hippel, ...

Author: Ikujirō Nonaka

Publisher: Oxford University Press on Demand

ISBN: 9780195130638

Category: Business & Economics

Page: 303

View: 880

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This book brings together the research of a number of scholars in the field of knowledge creation and imparts a sense of order to the field. The chapters share three characteristics: they are all grounded in extensive qualitative and/or quantitative research; they all go beyond the mere description of the knowledge-creation process and offer both theoretical and strategic implications; they share a view of knowledge creation and knowledge transfer as delicate processes, necessitating particular forms of support from managers.
2001 By Ikujirō Nonaka

Symbolic models of abductive reasoning tend to be far too searchintensive (e.g., Peng & Reggia, 1990), ... This chapter proposes a hybrid learning model for abduction that tightly integrates a symbolic Soar model (Newell, ...

Author: Ron Sun

Publisher: Psychology Press

ISBN: 9781134802067

Category: Psychology

Page: 392

View: 112

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A variety of ideas, approaches, and techniques exist -- in terms of both architecture and learning -- and this abundance seems to lead to many exciting possibilities in terms of theoretical advances and application potentials. Despite the apparent diversity, there is clearly an underlying unifying theme: architectures that bring together symbolic and connectionist models to achieve a synthesis and synergy of the two different paradigms, and the learning and knowledge acquisition methods for developing such architectures. More effort needs to be extended to exploit the possibilities and opportunities in this area. This book is the outgrowth of The IJCAI Workshop on Connectionist-Symbolic Integration: From Unified to Hybrid Approaches, held in conjunction with the fourteenth International Joint Conference on Artificial Intelligence (IJCAI '95). Featuring various presentations and discussions, this two-day workshop brought to light many new ideas, controversies, and syntheses which lead to the present volume. This book is concerned with the development, analysis, and application of hybrid connectionist-symbolic models in artificial intelligence and cognitive science. Drawing contributions from a large international group of experts, it describes and compares a variety of models in this area. The types of models discussed cover a wide range of the evolving spectrum of hybrid models, thus serving as a well-balanced progress report on the state of the art. As such, this volume provides an information clearinghouse for various proposed approaches and models that share the common belief that connectionist and symbolic models can be usefully combined and integrated, and such integration may lead to significant advances in understanding intelligence.
2013-04-15 By Ron Sun