Performance Evaluation And Benchmarking Of Intelligent Systems
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Performance Evaluation and Benchmarking of Intelligent Systems
Author: Raj Madhavan
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-09-18
To design and develop capable, dependable, and affordable intelligent systems, their performance must be measurable. Scienti?c methodologies for standardization and benchmarking are crucial for quantitatively evaluating the performance of eme- ing robotic and intelligent systems’ technologies. There is currently no accepted standard for quantitatively measuring the performance of these systems against user-de?ned requirements; and furthermore, there is no consensus on what obj- tive evaluation procedures need to be followed to understand the performance of these systems. The lack of reproducible and repeatable test methods has precluded researchers working towards a common goal from exchanging and communic- ing results, inter-comparing system performance, and leveraging previous work that could otherwise avoid duplication and expedite technology transfer. Currently, this lack of cohesion in the community hinders progress in many domains, such as m- ufacturing, service, healthcare, and security. By providing the research community with access to standardized tools, reference data sets, and open source libraries of solutions, researchers and consumers will be able to evaluate the cost and be- ?ts associated with intelligent systems and associated technologies. In this vein, the edited book volume addresses performance evaluation and metrics for intel- gent systems, in general, while emphasizing the need and solutions for standardized methods. To the knowledge of the editors, there is not a single book on the market that is solely dedicated to the subject of performance evaluation and benchmarking of intelligent systems.
Performance Evaluation and Benchmarking of Intelligent Systems
Author: Raj Madhavan
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-04-29
To design and develop capable, dependable, and affordable intelligent systems, their performance must be measurable. Scienti?c methodologies for standardization and benchmarking are crucial for quantitatively evaluating the performance of eme- ing robotic and intelligent systems’ technologies. There is currently no accepted standard for quantitatively measuring the performance of these systems against user-de?ned requirements; and furthermore, there is no consensus on what obj- tive evaluation procedures need to be followed to understand the performance of these systems. The lack of reproducible and repeatable test methods has precluded researchers working towards a common goal from exchanging and communic- ing results, inter-comparing system performance, and leveraging previous work that could otherwise avoid duplication and expedite technology transfer. Currently, this lack of cohesion in the community hinders progress in many domains, such as m- ufacturing, service, healthcare, and security. By providing the research community with access to standardized tools, reference data sets, and open source libraries of solutions, researchers and consumers will be able to evaluate the cost and be- ?ts associated with intelligent systems and associated technologies. In this vein, the edited book volume addresses performance evaluation and metrics for intel- gent systems, in general, while emphasizing the need and solutions for standardized methods. To the knowledge of the editors, there is not a single book on the market that is solely dedicated to the subject of performance evaluation and benchmarking of intelligent systems.
Autonomy and Artificial Intelligence: A Threat or Savior?
This book explores how Artificial Intelligence (AI), by leading to an increase in the autonomy of machines and robots, is offering opportunities for an expanded but uncertain impact on society by humans, machines, and robots. To help readers better understand the relationships between AI, autonomy, humans and machines that will help society reduce human errors in the use of advanced technologies (e.g., airplanes, trains, cars), this edited volume presents a wide selection of the underlying theories, computational models, experimental methods, and field applications. While other literature deals with these topics individually, this book unifies the fields of autonomy and AI, framing them in the broader context of effective integration for human-autonomous machine and robotic systems. The contributions, written by world-class researchers and scientists, elaborate on key research topics at the heart of effective human-machine-robot-systems integration. These topics include, for example, computational support for intelligence analyses; the challenge of verifying today’s and future autonomous systems; comparisons between today’s machines and autism; implications of human information interaction on artificial intelligence and errors; systems that reason; the autonomy of machines, robots, buildings; and hybrid teams, where hybrid reflects arbitrary combinations of humans, machines and robots. The contributors span the field of autonomous systems research, ranging from industry and academia to government. Given the broad diversity of the research in this book, the editors strove to thoroughly examine the challenges and trends of systems that implement and exhibit AI; the social implications of present and future systems made autonomous with AI; systems with AI seeking to develop trusted relationships among humans, machines, and robots; and the effective human systems integration that must result for trust in these new systems and their applications to increase and to be sustained.