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Applications of Learning & Planning Methods

Author: Nikolaos G. Bourbakis

Publisher: World Scientific

Published: 1991

Total Pages: 406

ISBN-13: 9789810205461

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Learning and planning are two important topics of artificial intelligence. Learning deals with the algorithmic processes that make a computing machine able to ?learn? and improve its performance during the process of complex tasks. Planning on the other hand, deals with decision and construction processes that make a machine capable of constructing an intelligent plan for the solution of a particular complex problem.This book combines both learning and planning methodologies and their applications in different domains. It is divided into two parts. The first part contains seven chapters on the ongoing research work in symbolic and connectionist learning. The second part includes seven chapters which provide the current research efforts in planning methodologies and their application to robotics.

Book Synopsis Applications of Learning & Planning Methods by : Nikolaos G. Bourbakis

Download or read book Applications of Learning & Planning Methods written by Nikolaos G. Bourbakis and published by World Scientific. This book was released on 1991 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning and planning are two important topics of artificial intelligence. Learning deals with the algorithmic processes that make a computing machine able to ?learn? and improve its performance during the process of complex tasks. Planning on the other hand, deals with decision and construction processes that make a machine capable of constructing an intelligent plan for the solution of a particular complex problem.This book combines both learning and planning methodologies and their applications in different domains. It is divided into two parts. The first part contains seven chapters on the ongoing research work in symbolic and connectionist learning. The second part includes seven chapters which provide the current research efforts in planning methodologies and their application to robotics.

Applications of Learning and Planning Methods

Author: N G Bourbakis

Publisher: World Scientific

Published: 1991-03-29

Total Pages: 392

ISBN-13: 9814506435

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Learning and planning are two important topics of artificial intelligence. Learning deals with the algorithmic processes that make a computing machine able to “learn” and improve its performance during the process of complex tasks. Planning on the other hand, deals with decision and construction processes that make a machine capable of constructing an intelligent plan for the solution of a particular complex problem. This book combines both learning and planning methodologies and their applications in different domains. It is divided into two parts. The first part contains seven chapters on the ongoing research work in symbolic and connectionist learning. The second part includes seven chapters which provide the current research efforts in planning methodologies and their application to robotics. Contents:An Introduction to Learning and Planning (N G Bourbakis)Embedding Learning in a General Frame-Based Architecture (T Tanaka & T M Mitchell)Connectionist Learning with CHEBYCHEV Networks and Analysis of its Internal Representation (A Namatame)Layered Inductive Learning Algorithms and their Computational Aspects (H Madala)An Approach to Combining Explanation-Based and Neural Learning Algorithms (J W Savlick & G G Towell)The Application of Symbolic Inductive Learning to the Acquisition and Recognition of Noisy Texture Concepts (P W Pachowicz)Automating Technology Adaptation in Design Synthesis (J R Kipps & D D Gajski)Connectionist Production Systems in Local and Hierarchical Representation (A Sohn & J L Gaudiot)A Parallel Architecture for AI Non-Linear Planning (S Lee & K Chung)Heuristic Tree Search Using Nonparametric Statistical Inference Methods (W Zhang & N S V Rao)An A∗ Approach to Robust Plan Recognition for Intelligent Interfaces (R J Calistri-Yeh)Differential A∗: An Adaptive Search Method Illustrated with Robot Path Planning for Moving Obstacles and Goals and an Uncertain Environment (K I Trovato)Path Planning Under Uncertainty (F Yegenoglu & H E Stephanou)Knowledge-Based Acquisition in Real-Time Path Planning in Unknown Space (N G Bourbakis)Path Planning for Two Cooperating Robot Manipulators (Q Xue & P C Y Sheu) Readership: Computer scientists, graduate students and researchers. keywords:

Book Synopsis Applications of Learning and Planning Methods by : N G Bourbakis

Download or read book Applications of Learning and Planning Methods written by N G Bourbakis and published by World Scientific. This book was released on 1991-03-29 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning and planning are two important topics of artificial intelligence. Learning deals with the algorithmic processes that make a computing machine able to “learn” and improve its performance during the process of complex tasks. Planning on the other hand, deals with decision and construction processes that make a machine capable of constructing an intelligent plan for the solution of a particular complex problem. This book combines both learning and planning methodologies and their applications in different domains. It is divided into two parts. The first part contains seven chapters on the ongoing research work in symbolic and connectionist learning. The second part includes seven chapters which provide the current research efforts in planning methodologies and their application to robotics. Contents:An Introduction to Learning and Planning (N G Bourbakis)Embedding Learning in a General Frame-Based Architecture (T Tanaka & T M Mitchell)Connectionist Learning with CHEBYCHEV Networks and Analysis of its Internal Representation (A Namatame)Layered Inductive Learning Algorithms and their Computational Aspects (H Madala)An Approach to Combining Explanation-Based and Neural Learning Algorithms (J W Savlick & G G Towell)The Application of Symbolic Inductive Learning to the Acquisition and Recognition of Noisy Texture Concepts (P W Pachowicz)Automating Technology Adaptation in Design Synthesis (J R Kipps & D D Gajski)Connectionist Production Systems in Local and Hierarchical Representation (A Sohn & J L Gaudiot)A Parallel Architecture for AI Non-Linear Planning (S Lee & K Chung)Heuristic Tree Search Using Nonparametric Statistical Inference Methods (W Zhang & N S V Rao)An A∗ Approach to Robust Plan Recognition for Intelligent Interfaces (R J Calistri-Yeh)Differential A∗: An Adaptive Search Method Illustrated with Robot Path Planning for Moving Obstacles and Goals and an Uncertain Environment (K I Trovato)Path Planning Under Uncertainty (F Yegenoglu & H E Stephanou)Knowledge-Based Acquisition in Real-Time Path Planning in Unknown Space (N G Bourbakis)Path Planning for Two Cooperating Robot Manipulators (Q Xue & P C Y Sheu) Readership: Computer scientists, graduate students and researchers. keywords:

Machine Learning Methods for Planning

Author: Steven Minton

Publisher: Morgan Kaufmann

Published: 2014-05-12

Total Pages: 555

ISBN-13: 1483221172

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Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning. Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credit assignment and describe tractable classes of problems for which optimal plans can be derived. This book discusses as well how reactive, integrated systems give rise to new requirements and opportunities for machine learning. The final chapter deals with a method for learning problem decompositions, which is based on an idealized model of efficiency for problem-reduction search. This book is a valuable resource for production managers, planners, scientists, and research workers.

Book Synopsis Machine Learning Methods for Planning by : Steven Minton

Download or read book Machine Learning Methods for Planning written by Steven Minton and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning. Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credit assignment and describe tractable classes of problems for which optimal plans can be derived. This book discusses as well how reactive, integrated systems give rise to new requirements and opportunities for machine learning. The final chapter deals with a method for learning problem decompositions, which is based on an idealized model of efficiency for problem-reduction search. This book is a valuable resource for production managers, planners, scientists, and research workers.

Research Anthology on Machine Learning Techniques, Methods, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2022-05-13

Total Pages: 1516

ISBN-13: 1668462923

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Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.

Book Synopsis Research Anthology on Machine Learning Techniques, Methods, and Applications by : Management Association, Information Resources

Download or read book Research Anthology on Machine Learning Techniques, Methods, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2022-05-13 with total page 1516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.

Intelligent Robotics and Applications

Author: Honghai Liu

Publisher: Springer Nature

Published: 2022-08-03

Total Pages: 801

ISBN-13: 3031138449

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The 4-volume set LNAI 13455 - 13458 constitutes the proceedings of the 15th International Conference on Intelligent Robotics and Applications, ICIRA 2022, which took place in Harbin China, during August 2022. The 284 papers included in these proceedings were carefully reviewed and selected from 442 submissions. They were organized in topical sections as follows: Robotics, Mechatronics, Applications, Robotic Machining, Medical Engineering, Soft and Hybrid Robots, Human-robot Collaboration, Machine Intelligence, and Human Robot Interaction.

Book Synopsis Intelligent Robotics and Applications by : Honghai Liu

Download or read book Intelligent Robotics and Applications written by Honghai Liu and published by Springer Nature. This book was released on 2022-08-03 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 4-volume set LNAI 13455 - 13458 constitutes the proceedings of the 15th International Conference on Intelligent Robotics and Applications, ICIRA 2022, which took place in Harbin China, during August 2022. The 284 papers included in these proceedings were carefully reviewed and selected from 442 submissions. They were organized in topical sections as follows: Robotics, Mechatronics, Applications, Robotic Machining, Medical Engineering, Soft and Hybrid Robots, Human-robot Collaboration, Machine Intelligence, and Human Robot Interaction.

Machine Learning Methods for Planning

Author: Steven Minton

Publisher: Morgan Kaufmann Publishers

Published: 1993

Total Pages: 566

ISBN-13:

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Research on planning systems has shown that domain knowledge is crucial for effectively coping with complex, changing environments. Unfortunately, acquiring and incorporating the necessary domain knowledge can be a significant problem when building a practical planning system. The knowledge engineering process is typically time-consuming and expensive. Furthermore, if a human expert is not available it may be extremely difficult to obtain the necessary knowledge. One solution is for a system to automatically acquire domain-specific knowledge through learning. The idea of a planning system that can improve its performance with experience is very attractive. Furthermore, advances in machine learning have provided a deeper understanding of learning mechanisms relevant to acquiring such knowledge. For this reason, there is a great deal of interest in this area of artificial intelligence. This book brings together, in one volume, a set of chapters from the primary researchers in the field, presenting a picture of its current state and its likely areas for application. The chapters describe a variety of learning methods

Book Synopsis Machine Learning Methods for Planning by : Steven Minton

Download or read book Machine Learning Methods for Planning written by Steven Minton and published by Morgan Kaufmann Publishers. This book was released on 1993 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on planning systems has shown that domain knowledge is crucial for effectively coping with complex, changing environments. Unfortunately, acquiring and incorporating the necessary domain knowledge can be a significant problem when building a practical planning system. The knowledge engineering process is typically time-consuming and expensive. Furthermore, if a human expert is not available it may be extremely difficult to obtain the necessary knowledge. One solution is for a system to automatically acquire domain-specific knowledge through learning. The idea of a planning system that can improve its performance with experience is very attractive. Furthermore, advances in machine learning have provided a deeper understanding of learning mechanisms relevant to acquiring such knowledge. For this reason, there is a great deal of interest in this area of artificial intelligence. This book brings together, in one volume, a set of chapters from the primary researchers in the field, presenting a picture of its current state and its likely areas for application. The chapters describe a variety of learning methods

Stochastic Complexity In Statistical Inquiry

Author: Jorma Rissanen

Publisher: World Scientific

Published: 1998-10-07

Total Pages: 191

ISBN-13: 9814507407

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This book describes how model selection and statistical inference can be founded on the shortest code length for the observed data, called the stochastic complexity. This generalization of the algorithmic complexity not only offers an objective view of statistics, where no prejudiced assumptions of 'true' data generating distributions are needed, but it also in one stroke leads to calculable expressions in a range of situations of practical interest and links very closely with mainstream statistical theory. The search for the smallest stochastic complexity extends the classical maximum likelihood technique to a new global one, in which models can be compared regardless of their numbers of parameters. The result is a natural and far reaching extension of the traditional theory of estimation, where the Fisher information is replaced by the stochastic complexity and the Cramer-Rao inequality by an extension of the Shannon-Kullback inequality. Ideas are illustrated with applications from parametric and non-parametric regression, density and spectrum estimation, time series, hypothesis testing, contingency tables, and data compression.

Book Synopsis Stochastic Complexity In Statistical Inquiry by : Jorma Rissanen

Download or read book Stochastic Complexity In Statistical Inquiry written by Jorma Rissanen and published by World Scientific. This book was released on 1998-10-07 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes how model selection and statistical inference can be founded on the shortest code length for the observed data, called the stochastic complexity. This generalization of the algorithmic complexity not only offers an objective view of statistics, where no prejudiced assumptions of 'true' data generating distributions are needed, but it also in one stroke leads to calculable expressions in a range of situations of practical interest and links very closely with mainstream statistical theory. The search for the smallest stochastic complexity extends the classical maximum likelihood technique to a new global one, in which models can be compared regardless of their numbers of parameters. The result is a natural and far reaching extension of the traditional theory of estimation, where the Fisher information is replaced by the stochastic complexity and the Cramer-Rao inequality by an extension of the Shannon-Kullback inequality. Ideas are illustrated with applications from parametric and non-parametric regression, density and spectrum estimation, time series, hypothesis testing, contingency tables, and data compression.

Computer-Assisted Language Learning: Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2019-01-04

Total Pages: 2194

ISBN-13: 1522576649

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In a diverse society, the ability to cross communication barriers is critical to the success of any individual personally, professionally, and academically. With the constant acceleration of course programs and technology, educators are continually being challenged to develop and implement creative methods for engaging English-speaking and non-English-speaking learners. Computer-Assisted Language Learning: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines the relationship between language education and technology and the potential for curriculum enhancements through the use of mobile technologies, flipped instruction, and language-learning software. This multi-volume book is geared toward educators, researchers, academics, linguists, and upper-level students seeking relevant research on the improvement of language education through the use of technology.

Book Synopsis Computer-Assisted Language Learning: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Computer-Assisted Language Learning: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2019-01-04 with total page 2194 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a diverse society, the ability to cross communication barriers is critical to the success of any individual personally, professionally, and academically. With the constant acceleration of course programs and technology, educators are continually being challenged to develop and implement creative methods for engaging English-speaking and non-English-speaking learners. Computer-Assisted Language Learning: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines the relationship between language education and technology and the potential for curriculum enhancements through the use of mobile technologies, flipped instruction, and language-learning software. This multi-volume book is geared toward educators, researchers, academics, linguists, and upper-level students seeking relevant research on the improvement of language education through the use of technology.

Planning Algorithms

Author: Steven Michael LaValle

Publisher:

Published: 2006

Total Pages: 826

ISBN-13: 9780511241338

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Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that integrates literature from several fields into a coherent source for teaching and reference in applications including robotics, computational biology, computer graphics, manufacturing, aerospace applications, and medicine.

Book Synopsis Planning Algorithms by : Steven Michael LaValle

Download or read book Planning Algorithms written by Steven Michael LaValle and published by . This book was released on 2006 with total page 826 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that integrates literature from several fields into a coherent source for teaching and reference in applications including robotics, computational biology, computer graphics, manufacturing, aerospace applications, and medicine.

Teacher Education: Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

Published: 2016-05-19

Total Pages: 1663

ISBN-13: 1522501657

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Educators play a significant role in the intellectual and social development of children and young adults. Next-generation teachers can only be as strong as their own educational foundation which serves to cultivate their knowledge of the learning process, uncover best practices in the field of education, and employ leadership abilities that will inspire students of all ages. Teacher Education: Concepts, Methodologies, Tools, and Applications explores the current state of pre-service teacher programs as well as continuing education initiatives for in-service educators. Emphasizing the growing role of technology in teacher skill development and training as well as key teaching methods and pedagogical developments, this multi-volume work compiles research essential to higher education professionals and administrators, educational software developers, and researchers studying pre-service and in-service teacher training.

Book Synopsis Teacher Education: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Teacher Education: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2016-05-19 with total page 1663 pages. Available in PDF, EPUB and Kindle. Book excerpt: Educators play a significant role in the intellectual and social development of children and young adults. Next-generation teachers can only be as strong as their own educational foundation which serves to cultivate their knowledge of the learning process, uncover best practices in the field of education, and employ leadership abilities that will inspire students of all ages. Teacher Education: Concepts, Methodologies, Tools, and Applications explores the current state of pre-service teacher programs as well as continuing education initiatives for in-service educators. Emphasizing the growing role of technology in teacher skill development and training as well as key teaching methods and pedagogical developments, this multi-volume work compiles research essential to higher education professionals and administrators, educational software developers, and researchers studying pre-service and in-service teacher training.