Download Learning And Reasoning With Complex Representations full books in PDF, epub, and Kindle. Read online free Learning And Reasoning With Complex Representations ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : |
| Publisher | : Routledge |
| Total Pages | : 271 |
| Release | : 2010 |
| Genre | : Interaction analysis in education |
| ISBN | : 1136943994 |
Within an increasingly multimedia focused society, the use of external representations in learning, teaching and communication has increased dramatically. This book explores: how we can theorise the relationship between processing internal and external representations.
| Author | : John K. Gilbert |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 326 |
| Release | : 2007-12-05 |
| Genre | : Education |
| ISBN | : 1402052677 |
External representations (pictures, diagrams, graphs, concrete models) have always been valuable tools for the science teacher. This book brings together the insights of practicing scientists, science education researchers, computer specialists, and cognitive scientists, to produce a coherent overview. It links presentations about cognitive theory, its implications for science curriculum design, and for learning and teaching in classrooms and laboratories.
| Author | : Ronald Brachman |
| Publisher | : Morgan Kaufmann |
| Total Pages | : 414 |
| Release | : 2004-05-19 |
| Genre | : Computers |
| ISBN | : 1558609326 |
Knowledge representation is at the very core of a radical idea for understanding intelligence. This book talks about the central concepts of knowledge representation developed over the years. It is suitable for researchers and practitioners in database management, information retrieval, object-oriented systems and artificial intelligence.
| Author | : Zhiyuan Liu |
| Publisher | : Springer Nature |
| Total Pages | : 535 |
| Release | : 2023-08-23 |
| Genre | : Computers |
| ISBN | : 9819916003 |
This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV 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. As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book.
| Author | : Janet Kolodner |
| Publisher | : Morgan Kaufmann |
| Total Pages | : 687 |
| Release | : 2014-06-28 |
| Genre | : Computers |
| ISBN | : 1483294498 |
Case-based reasoning is one of the fastest growing areas in the field of knowledge-based systems and this book, authored by a leader in the field, is the first comprehensive text on the subject. Case-based reasoning systems are systems that store information about situations in their memory. As new problems arise, similar situations are searched out to help solve these problems. Problems are understood and inferences are made by finding the closest cases in memory, comparing and contrasting the problem with those cases, making inferences based on those comparisons, and asking questions when inferences can't be made. This book presents the state of the art in case-based reasoning. The author synthesizes and analyzes a broad range of approaches, with special emphasis on applying case-based reasoning to complex real-world problem-solving tasks such as medical diagnosis, design, conflict resolution, and planning. The author's approach combines cognitive science and engineering, and is based on analysis of both expert and common-sense tasks. Guidelines for building case-based expert systems are provided, such as how to represent knowledge in cases, how to index cases for accessibility, how to implement retrieval processes for efficiency, and how to adapt old solutions to fit new situations. This book is an excellent text for courses and tutorials on case-based reasoning. It is also a useful resource for computer professionals and cognitive scientists interested in learning more about this fast-growing field.
| Author | : George McCloskey |
| Publisher | : John Wiley & Sons |
| Total Pages | : 356 |
| Release | : 2012-12-14 |
| Genre | : Psychology |
| ISBN | : 1118281837 |
Written by experts in the area of executive functioning, Essentials of Executive Functions Assessment equips mental health practitioners (school, clinical, developmental/pediatric, neuropsychologists, educational diagnosticians, and educational therapists) with all the information they need to administer, score, and interpret assessment instruments that test for executive functions deficits associated with a number of psychiatric and developmental disorders.
| Author | : Orit Ben Zvi Assaraf |
| Publisher | : Springer Nature |
| Total Pages | : 283 |
| Release | : 2022-05-25 |
| Genre | : Science |
| ISBN | : 3030981444 |
This book synthesizes a wealth of international research on the critical topic of ‘fostering understanding of complex systems in biology education’. Complex systems are prevalent in many scientific fields, and at all scales, from the micro scale of a single cell or molecule to complex systems at the macro scale such as ecosystems. Understanding the complexity of natural systems can be extremely challenging, though crucial for an adequate understanding of what they are and how they work. The term “systems thinking” has become synonymous with developing a coherent understanding of complex biological processes and phenomena. For researchers and educators alike, understanding how students’ systems thinking develops is an essential prerequisite to develop and maintain pedagogical scaffolding that facilitates students’ ability to fully understand the system’s complexity. To that end, this book provides researchers and teachers with key insights from the current research community on how to support learners systems thinking in secondary and higher education. Each chapter in the book elaborates on different theoretical and methodological frameworks pertaining to complexity in biology education and a variety of biological topics are included from genetics, photosynthesis, and the carbon cycle to ecology and climate change. Specific attention is paid to design elements of computer-based learning environments to understand complexity in biology education.
| Author | : Andreas Tolk |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 272 |
| Release | : 2009-01-17 |
| Genre | : Mathematics |
| ISBN | : 3540880747 |
The tremendous growth in the availability of inexpensive computing power and easy availability of computers have generated tremendous interest in the design and imp- mentation of Complex Systems. Computer-based solutions offer great support in the design of Complex Systems. Furthermore, Complex Systems are becoming incre- ingly complex themselves. This research book comprises a selection of state-of-the-art contributions to topics dealing with Complex Systems in a Knowledge-based En- ronment. Complex systems are ubiquitous. Examples comprise, but are not limited to System of Systems, Service-oriented Approaches, Agent-based Systems, and Complex Distributed Virtual Systems. These are application domains that require knowledge of engineering and management methods and are beyond the scope of traditional systems. The chapters in this book deal with a selection of topics which range from unc- tainty representation, management and the use of ontological means which support and are large-scale business integration. All contributions were invited and are based on the recognition of the expertise of the contributing authors in the field. By colle- ing these sources together in one volume, the intention was to present a variety of tools to the reader to assist in both study and work. The second intention was to show how the different facets presented in the chapters are complementary and contribute towards this emerging discipline designed to aid in the analysis of complex systems.
| Author | : Ron Sun |
| Publisher | : Psychology Press |
| Total Pages | : 391 |
| Release | : 2013-04-15 |
| Genre | : Psychology |
| ISBN | : 1134802064 |
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.
