Author: Nikolas G Bourbakis
Publisher: World Scientific
ISBN: 9814506435
Category : Computers
Languages : en
Pages : 393
Book Description
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: Nikolas G Bourbakis
Publisher: World Scientific
ISBN: 9814506435
Category : Computers
Languages : en
Pages : 393
Book Description
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.
Publisher: World Scientific
ISBN: 9814506435
Category : Computers
Languages : en
Pages : 393
Book Description
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.
Machine Learning Methods for Planning
Author: Steven Minton
Publisher: Morgan Kaufmann
ISBN: 1483221172
Category : Social Science
Languages : en
Pages : 555
Book Description
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.
Publisher: Morgan Kaufmann
ISBN: 1483221172
Category : Social Science
Languages : en
Pages : 555
Book Description
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.
Understanding by Design
Author: Grant P. Wiggins
Publisher: ASCD
ISBN: 1416600353
Category : Education
Languages : en
Pages : 383
Book Description
What is understanding and how does it differ from knowledge? How can we determine the big ideas worth understanding? Why is understanding an important teaching goal, and how do we know when students have attained it? How can we create a rigorous and engaging curriculum that focuses on understanding and leads to improved student performance in today's high-stakes, standards-based environment? Authors Grant Wiggins and Jay McTighe answer these and many other questions in this second edition of Understanding by Design. Drawing on feedback from thousands of educators around the world who have used the UbD framework since its introduction in 1998, the authors have greatly revised and expanded their original work to guide educators across the K-16 spectrum in the design of curriculum, assessment, and instruction. With an improved UbD Template at its core, the book explains the rationale of backward design and explores in greater depth the meaning of such key ideas as essential questions and transfer tasks. Readers will learn why the familiar coverage- and activity-based approaches to curriculum design fall short, and how a focus on the six facets of understanding can enrich student learning. With an expanded array of practical strategies, tools, and examples from all subject areas, the book demonstrates how the research-based principles of Understanding by Design apply to district frameworks as well as to individual units of curriculum. Combining provocative ideas, thoughtful analysis, and tested approaches, this new edition of Understanding by Design offers teacher-designers a clear path to the creation of curriculum that ensures better learning and a more stimulating experience for students and teachers alike.
Publisher: ASCD
ISBN: 1416600353
Category : Education
Languages : en
Pages : 383
Book Description
What is understanding and how does it differ from knowledge? How can we determine the big ideas worth understanding? Why is understanding an important teaching goal, and how do we know when students have attained it? How can we create a rigorous and engaging curriculum that focuses on understanding and leads to improved student performance in today's high-stakes, standards-based environment? Authors Grant Wiggins and Jay McTighe answer these and many other questions in this second edition of Understanding by Design. Drawing on feedback from thousands of educators around the world who have used the UbD framework since its introduction in 1998, the authors have greatly revised and expanded their original work to guide educators across the K-16 spectrum in the design of curriculum, assessment, and instruction. With an improved UbD Template at its core, the book explains the rationale of backward design and explores in greater depth the meaning of such key ideas as essential questions and transfer tasks. Readers will learn why the familiar coverage- and activity-based approaches to curriculum design fall short, and how a focus on the six facets of understanding can enrich student learning. With an expanded array of practical strategies, tools, and examples from all subject areas, the book demonstrates how the research-based principles of Understanding by Design apply to district frameworks as well as to individual units of curriculum. Combining provocative ideas, thoughtful analysis, and tested approaches, this new edition of Understanding by Design offers teacher-designers a clear path to the creation of curriculum that ensures better learning and a more stimulating experience for students and teachers alike.
Planning Algorithms
Author: Steven M. LaValle
Publisher: Cambridge University Press
ISBN: 9780521862059
Category : Computers
Languages : en
Pages : 844
Book Description
Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations.
Publisher: Cambridge University Press
ISBN: 9780521862059
Category : Computers
Languages : en
Pages : 844
Book Description
Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations.
Learning for Adaptive and Reactive Robot Control
Author: Aude Billard
Publisher: MIT Press
ISBN: 0262367017
Category : Technology & Engineering
Languages : en
Pages : 425
Book Description
Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.
Publisher: MIT Press
ISBN: 0262367017
Category : Technology & Engineering
Languages : en
Pages : 425
Book Description
Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.
Innovative Approaches to Planning, Scheduling and Control
Author: Katia P. Sycara
Publisher: Morgan Kaufmann
ISBN: 9781558601642
Category : Computers
Languages : en
Pages : 532
Book Description
Publisher: Morgan Kaufmann
ISBN: 9781558601642
Category : Computers
Languages : en
Pages : 532
Book Description
A Concise Introduction to Models and Methods for Automated Planning
Author: Hector Radanovic
Publisher: Springer Nature
ISBN: 3031015649
Category : Computers
Languages : en
Pages : 132
Book Description
Planning is the model-based approach to autonomous behavior where the agent behavior is derived automatically from a model of the actions, sensors, and goals. The main challenges in planning are computational as all models, whether featuring uncertainty and feedback or not, are intractable in the worst case when represented in compact form. In this book, we look at a variety of models used in AI planning, and at the methods that have been developed for solving them. The goal is to provide a modern and coherent view of planning that is precise, concise, and mostly self-contained, without being shallow. For this, we make no attempt at covering the whole variety of planning approaches, ideas, and applications, and focus on the essentials. The target audience of the book are students and researchers interested in autonomous behavior and planning from an AI, engineering, or cognitive science perspective. Table of Contents: Preface / Planning and Autonomous Behavior / Classical Planning: Full Information and Deterministic Actions / Classical Planning: Variations and Extensions / Beyond Classical Planning: Transformations / Planning with Sensing: Logical Models / MDP Planning: Stochastic Actions and Full Feedback / POMDP Planning: Stochastic Actions and Partial Feedback / Discussion / Bibliography / Author's Biography
Publisher: Springer Nature
ISBN: 3031015649
Category : Computers
Languages : en
Pages : 132
Book Description
Planning is the model-based approach to autonomous behavior where the agent behavior is derived automatically from a model of the actions, sensors, and goals. The main challenges in planning are computational as all models, whether featuring uncertainty and feedback or not, are intractable in the worst case when represented in compact form. In this book, we look at a variety of models used in AI planning, and at the methods that have been developed for solving them. The goal is to provide a modern and coherent view of planning that is precise, concise, and mostly self-contained, without being shallow. For this, we make no attempt at covering the whole variety of planning approaches, ideas, and applications, and focus on the essentials. The target audience of the book are students and researchers interested in autonomous behavior and planning from an AI, engineering, or cognitive science perspective. Table of Contents: Preface / Planning and Autonomous Behavior / Classical Planning: Full Information and Deterministic Actions / Classical Planning: Variations and Extensions / Beyond Classical Planning: Transformations / Planning with Sensing: Logical Models / MDP Planning: Stochastic Actions and Full Feedback / POMDP Planning: Stochastic Actions and Partial Feedback / Discussion / Bibliography / Author's Biography
Artificial Intelligence: Methodology, Systems, and Applications
Author: Allan Ramsay
Publisher: Springer
ISBN: 3642331858
Category : Computers
Languages : en
Pages : 346
Book Description
This book constitutes the refereed proceedings of the 15th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2012, held in Varna, Bulgaria in September 2012. The 36 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on natural language processing, social networks, knowledge representation and reasoning, machine learning, planning and agents, search, and computer vision.
Publisher: Springer
ISBN: 3642331858
Category : Computers
Languages : en
Pages : 346
Book Description
This book constitutes the refereed proceedings of the 15th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2012, held in Varna, Bulgaria in September 2012. The 36 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on natural language processing, social networks, knowledge representation and reasoning, machine learning, planning and agents, search, and computer vision.
Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
Author: Olivas, Emilio Soria
Publisher: IGI Global
ISBN: 1605667676
Category : Computers
Languages : en
Pages : 734
Book Description
"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.
Publisher: IGI Global
ISBN: 1605667676
Category : Computers
Languages : en
Pages : 734
Book Description
"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.
Informatics in Control, Automation and Robotics
Author: Giuseppina Gini
Publisher: Springer Nature
ISBN: 3031483030
Category : Technology & Engineering
Languages : en
Pages : 158
Book Description
The book focuses the latest endeavors relating researches and developments conducted in fields of control, robotics, and automation. Through ten revised and extended articles, the present book aims to provide the most up-to-date state-of-the-art of the aforementioned fields allowing researcher, Ph.D. students, and engineers not only updating their knowledge but also benefiting from the source of inspiration that represents the set of selected articles of the book. The deliberate intention of editors to cover as well theoretical facets of those fields as their practical accomplishments and implementations offers the benefit of gathering in a same volume a factual and well-balanced prospect of nowadays research in those topics. A special attention toward “Intelligent Robots and Control” may characterize another benefit of this book.
Publisher: Springer Nature
ISBN: 3031483030
Category : Technology & Engineering
Languages : en
Pages : 158
Book Description
The book focuses the latest endeavors relating researches and developments conducted in fields of control, robotics, and automation. Through ten revised and extended articles, the present book aims to provide the most up-to-date state-of-the-art of the aforementioned fields allowing researcher, Ph.D. students, and engineers not only updating their knowledge but also benefiting from the source of inspiration that represents the set of selected articles of the book. The deliberate intention of editors to cover as well theoretical facets of those fields as their practical accomplishments and implementations offers the benefit of gathering in a same volume a factual and well-balanced prospect of nowadays research in those topics. A special attention toward “Intelligent Robots and Control” may characterize another benefit of this book.