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Qualitative Spatial Abstraction in Reinforcement Learning

Author: Lutz Frommberger

Publisher: Springer Science & Business Media

Published: 2010-12-13

Total Pages: 186

ISBN-13: 3642165907

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Reinforcement learning has developed as a successful learning approach for domains that are not fully understood and that are too complex to be described in closed form. However, reinforcement learning does not scale well to large and continuous problems. Furthermore, acquired knowledge specific to the learned task, and transfer of knowledge to new tasks is crucial. In this book the author investigates whether deficiencies of reinforcement learning can be overcome by suitable abstraction methods. He discusses various forms of spatial abstraction, in particular qualitative abstraction, a form of representing knowledge that has been thoroughly investigated and successfully applied in spatial cognition research. With his approach, he exploits spatial structures and structural similarity to support the learning process by abstracting from less important features and stressing the essential ones. The author demonstrates his learning approach and the transferability of knowledge by having his system learn in a virtual robot simulation system and consequently transfer the acquired knowledge to a physical robot. The approach is influenced by findings from cognitive science. The book is suitable for researchers working in artificial intelligence, in particular knowledge representation, learning, spatial cognition, and robotics.

Book Synopsis Qualitative Spatial Abstraction in Reinforcement Learning by : Lutz Frommberger

Download or read book Qualitative Spatial Abstraction in Reinforcement Learning written by Lutz Frommberger and published by Springer Science & Business Media. This book was released on 2010-12-13 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning has developed as a successful learning approach for domains that are not fully understood and that are too complex to be described in closed form. However, reinforcement learning does not scale well to large and continuous problems. Furthermore, acquired knowledge specific to the learned task, and transfer of knowledge to new tasks is crucial. In this book the author investigates whether deficiencies of reinforcement learning can be overcome by suitable abstraction methods. He discusses various forms of spatial abstraction, in particular qualitative abstraction, a form of representing knowledge that has been thoroughly investigated and successfully applied in spatial cognition research. With his approach, he exploits spatial structures and structural similarity to support the learning process by abstracting from less important features and stressing the essential ones. The author demonstrates his learning approach and the transferability of knowledge by having his system learn in a virtual robot simulation system and consequently transfer the acquired knowledge to a physical robot. The approach is influenced by findings from cognitive science. The book is suitable for researchers working in artificial intelligence, in particular knowledge representation, learning, spatial cognition, and robotics.

Machine Learning and Data Mining in Pattern Recognition

Author: Petra Perner

Publisher: Springer

Published: 2018-07-09

Total Pages: 470

ISBN-13: 3319961365

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This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner

Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2018-07-09 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Architecture and Urbanism: A Smart Outlook

Author: Shaimaa Kamel

Publisher: Springer Nature

Published: 2020-11-02

Total Pages: 500

ISBN-13: 3030525848

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This proceedings addresses the challenges of urbanization that gravely affect the world’s ecosystems. To become efficiently sustainable and regenerative, buildings and cities need to adopt smart solutions. This book discusses innovations of the built environment while depicting how such practices can transform future buildings and urban areas into places of higher value and quality. The book aims to examine the interrelationship between people, nature and technology, which is essential in pursuing smart environments that optimize human wellbeing, motivation and vitality, as well as promoting cohesive and inclusive societies: Urban Sociology - Community Involvement - Place-making and Cultural Continuity – Environmental Psychology - Smart living - Just City. The book presents exemplary practical experiences that reflect smart strategies, technologies and innovations, by established and emerging professionals, provides a forum of real-life discourse. The primary audience for the work will be from the fields of architecture, urban planning and built-environment systems, including multi-disciplinary academics as well as professionals.

Book Synopsis Architecture and Urbanism: A Smart Outlook by : Shaimaa Kamel

Download or read book Architecture and Urbanism: A Smart Outlook written by Shaimaa Kamel and published by Springer Nature. This book was released on 2020-11-02 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings addresses the challenges of urbanization that gravely affect the world’s ecosystems. To become efficiently sustainable and regenerative, buildings and cities need to adopt smart solutions. This book discusses innovations of the built environment while depicting how such practices can transform future buildings and urban areas into places of higher value and quality. The book aims to examine the interrelationship between people, nature and technology, which is essential in pursuing smart environments that optimize human wellbeing, motivation and vitality, as well as promoting cohesive and inclusive societies: Urban Sociology - Community Involvement - Place-making and Cultural Continuity – Environmental Psychology - Smart living - Just City. The book presents exemplary practical experiences that reflect smart strategies, technologies and innovations, by established and emerging professionals, provides a forum of real-life discourse. The primary audience for the work will be from the fields of architecture, urban planning and built-environment systems, including multi-disciplinary academics as well as professionals.

Abstraction in Artificial Intelligence and Complex Systems

Author: Lorenza Saitta

Publisher: Springer Science & Business Media

Published: 2013-06-05

Total Pages: 488

ISBN-13: 1461470528

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Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences. After discussing the characterizing properties of abstraction, a formal model, the KRA model, is presented to capture them. This model makes the notion of abstraction easily applicable by means of the introduction of a set of abstraction operators and abstraction patterns, reusable across different domains and applications. It is the impact of abstraction in Artificial Intelligence, Complex Systems and Machine Learning which creates the core of the book. A general framework, based on the KRA model, is presented, and its pragmatic power is illustrated with three case studies: Model-based diagnosis, Cartographic Generalization, and learning Hierarchical Hidden Markov Models.

Book Synopsis Abstraction in Artificial Intelligence and Complex Systems by : Lorenza Saitta

Download or read book Abstraction in Artificial Intelligence and Complex Systems written by Lorenza Saitta and published by Springer Science & Business Media. This book was released on 2013-06-05 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences. After discussing the characterizing properties of abstraction, a formal model, the KRA model, is presented to capture them. This model makes the notion of abstraction easily applicable by means of the introduction of a set of abstraction operators and abstraction patterns, reusable across different domains and applications. It is the impact of abstraction in Artificial Intelligence, Complex Systems and Machine Learning which creates the core of the book. A general framework, based on the KRA model, is presented, and its pragmatic power is illustrated with three case studies: Model-based diagnosis, Cartographic Generalization, and learning Hierarchical Hidden Markov Models.

Representing Space in Cognition

Author: Thora Tenbrink

Publisher: Oxford University Press

Published: 2013-10

Total Pages: 325

ISBN-13: 0199679916

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This book considers how people talk about their environment, find their way in new surroundings, and plan routes. Leading scholars and researchers in psychology, linguistics, computer science, and geography show how empirical research can be used to inform formal approaches towards the development of intuitive assistance systems.

Book Synopsis Representing Space in Cognition by : Thora Tenbrink

Download or read book Representing Space in Cognition written by Thora Tenbrink and published by Oxford University Press. This book was released on 2013-10 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers how people talk about their environment, find their way in new surroundings, and plan routes. Leading scholars and researchers in psychology, linguistics, computer science, and geography show how empirical research can be used to inform formal approaches towards the development of intuitive assistance systems.

Spatial Cognition VI. Learning, Reasoning, and Talking about Space

Author: Christian Freksa

Publisher: Springer Science & Business Media

Published: 2008-09-10

Total Pages: 455

ISBN-13: 3540876006

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This book constitutes the refereed proceedings of the International Conference on Spatial Cognition, Spatial Cognition 2008, held in Freiburg, Germany, in September 2008. The 27 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from 54 submissions. The papers are organized in topical sections on spatial orientation, spatial navigation, spatial learning, maps and modalities, spatial communication, spatial language, similarity and abstraction, concepts and reference frames, as well as spatial modeling and spatial reasoning.

Book Synopsis Spatial Cognition VI. Learning, Reasoning, and Talking about Space by : Christian Freksa

Download or read book Spatial Cognition VI. Learning, Reasoning, and Talking about Space written by Christian Freksa and published by Springer Science & Business Media. This book was released on 2008-09-10 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Conference on Spatial Cognition, Spatial Cognition 2008, held in Freiburg, Germany, in September 2008. The 27 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from 54 submissions. The papers are organized in topical sections on spatial orientation, spatial navigation, spatial learning, maps and modalities, spatial communication, spatial language, similarity and abstraction, concepts and reference frames, as well as spatial modeling and spatial reasoning.

Qualitative Spatial Reasoning with Topological Information

Author: Jochen Renz

Publisher: Springer Science & Business Media

Published: 2002-02-27

Total Pages: 219

ISBN-13: 3540433465

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Spatial knowledge representation and reasoning with spatial knowledge are relevant issues for many application areas such as robotics, geographical information systems, and computer vision. Exceeding purely quantitative approaches, more recently initiated qualitative approaches allow for dealing with spatial information on a more abstract level that is closer to the way humans think and speak. Starting out with the qualitative, topological constraint calculus RCC8 proposed by Randell, Cui, and Cohn, this work presents answers to a variety of open questions regarding RCC8. The open issues concerning computational properties are solved by exploiting a broad variety of results and methods from logic and theoretical computer science. Questions concerning practical performance are addressed by large-scale empirical computational experiments. The most impressive result is probably the complete classification of computational properties for all fragments of RCC8.

Book Synopsis Qualitative Spatial Reasoning with Topological Information by : Jochen Renz

Download or read book Qualitative Spatial Reasoning with Topological Information written by Jochen Renz and published by Springer Science & Business Media. This book was released on 2002-02-27 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial knowledge representation and reasoning with spatial knowledge are relevant issues for many application areas such as robotics, geographical information systems, and computer vision. Exceeding purely quantitative approaches, more recently initiated qualitative approaches allow for dealing with spatial information on a more abstract level that is closer to the way humans think and speak. Starting out with the qualitative, topological constraint calculus RCC8 proposed by Randell, Cui, and Cohn, this work presents answers to a variety of open questions regarding RCC8. The open issues concerning computational properties are solved by exploiting a broad variety of results and methods from logic and theoretical computer science. Questions concerning practical performance are addressed by large-scale empirical computational experiments. The most impressive result is probably the complete classification of computational properties for all fragments of RCC8.

Qualitative Representation of Spatial Knowledge

Author: Daniel Hernandez

Publisher: Springer Science & Business Media

Published: 1994-06-28

Total Pages: 220

ISBN-13: 9783540580584

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This book develops, for the first time, a qualitative model for the representation of spatial knowledge based only on locative relations between the objects involved. The core of this book is devoted to the study of qualitative inference methods that take into account the rich structure of space. These methods can be applied to quite a number of areas characterized by uncertain or incomplete knowledge, as for example geographic information systems, robot control, computer-aided architectural design, and natural language information systems.

Book Synopsis Qualitative Representation of Spatial Knowledge by : Daniel Hernandez

Download or read book Qualitative Representation of Spatial Knowledge written by Daniel Hernandez and published by Springer Science & Business Media. This book was released on 1994-06-28 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops, for the first time, a qualitative model for the representation of spatial knowledge based only on locative relations between the objects involved. The core of this book is devoted to the study of qualitative inference methods that take into account the rich structure of space. These methods can be applied to quite a number of areas characterized by uncertain or incomplete knowledge, as for example geographic information systems, robot control, computer-aided architectural design, and natural language information systems.

Machine Learning

Author: Tom M. Mitchell

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 413

ISBN-13: 1461322790

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One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed.

Book Synopsis Machine Learning by : Tom M. Mitchell

Download or read book Machine Learning written by Tom M. Mitchell and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed.

Intelligent Robotics and Applications

Author: Caihua Xiong

Publisher: Springer

Published: 2008-10-14

Total Pages: 1315

ISBN-13: 3540885137

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These two volumes constitute the refereed proceedings of the First International Conference on Intelligent Robotics and Applications, ICIRA 2008, held in Wuhan, China, in October 2008. The 265 revised full papers presented were thoroughly reviewed and selected from 552 submissions; they are devoted but not limited to robot motion planning and manipulation; robot control; cognitive robotics; rehabilitation robotics; health care and artificial limb; robot learning; robot vision; human-machine interaction & coordination; mobile robotics; micro/nano mechanical systems; manufacturing automation; multi-axis surface machining; realworld applications.

Book Synopsis Intelligent Robotics and Applications by : Caihua Xiong

Download or read book Intelligent Robotics and Applications written by Caihua Xiong and published by Springer. This book was released on 2008-10-14 with total page 1315 pages. Available in PDF, EPUB and Kindle. Book excerpt: These two volumes constitute the refereed proceedings of the First International Conference on Intelligent Robotics and Applications, ICIRA 2008, held in Wuhan, China, in October 2008. The 265 revised full papers presented were thoroughly reviewed and selected from 552 submissions; they are devoted but not limited to robot motion planning and manipulation; robot control; cognitive robotics; rehabilitation robotics; health care and artificial limb; robot learning; robot vision; human-machine interaction & coordination; mobile robotics; micro/nano mechanical systems; manufacturing automation; multi-axis surface machining; realworld applications.