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Название: Metareasoning for Robots: Adapting in Dynamic and Uncertain Environments
Автор: Jeffrey W. Herrmann
Издательство: Springer
Год: 2023
Страниц: 102
Язык: английский
Формат: pdf (true), epub
Размер: 16.8 MB
This book is a state of the art resource that robotics researchers and engineers can use to make their robots and autonomous vehicles smarter. Readers will be able to describe metareasoning, select an appropriate metareasoning approach, and synthesize metareasoning policies. Metareasoning for Robots adopts a systems engineering perspective in which metareasoning is an approach that can improve the overall robot or autonomous system, not just one component or subsystem. This book introduces key concepts, discusses design options for metareasoning approaches and policies, and presents approaches for testing and evaluation of metareasoning policies. This book is for engineers and programmers who wish to design a better robot. It describes Metareasoning, a type of Artificial Intelligence (AI) that one can use to improve the robot’s ability to reason in the face of its limited resources and in a dynamic, uncertain environment. Metareasoning can select the best planning algorithm, recover from a reasoning process failure, and adjust the parameters of a reasoning algorithm. Although metareasoning has been discussed for many years, only now are engineers and programmers beginning to use it to design more intelligent robots that are safer and more reliable.
Автор: Jeffrey W. Herrmann
Издательство: Springer
Год: 2023
Страниц: 102
Язык: английский
Формат: pdf (true), epub
Размер: 16.8 MB
This book is a state of the art resource that robotics researchers and engineers can use to make their robots and autonomous vehicles smarter. Readers will be able to describe metareasoning, select an appropriate metareasoning approach, and synthesize metareasoning policies. Metareasoning for Robots adopts a systems engineering perspective in which metareasoning is an approach that can improve the overall robot or autonomous system, not just one component or subsystem. This book introduces key concepts, discusses design options for metareasoning approaches and policies, and presents approaches for testing and evaluation of metareasoning policies. This book is for engineers and programmers who wish to design a better robot. It describes Metareasoning, a type of Artificial Intelligence (AI) that one can use to improve the robot’s ability to reason in the face of its limited resources and in a dynamic, uncertain environment. Metareasoning can select the best planning algorithm, recover from a reasoning process failure, and adjust the parameters of a reasoning algorithm. Although metareasoning has been discussed for many years, only now are engineers and programmers beginning to use it to design more intelligent robots that are safer and more reliable.