Elena Messina

Raj Madhavan

Edward Tunstel

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

John Hallam

Angel P. del Pobil

Fabio Bonsignorio

This book focuses on a critical issue in the study of physical agents, whether natural or artificial: the quantitative modelling of sensory–motor coordination. Adopting a novel approach, it defines a common scientific framework for both the intelligent systems designed by engineers and those that have evolved naturally. As such it contributes to the widespread adoption of a rigorous quantitative and refutable approach in the scientific study of ‘embodied’ intelligence and cognition. More than 70 years after Norbert Wiener’s famous book Cybernetics: or Control and Communication in the Animal and the Machine (1948), robotics, AI and life sciences seem to be converging towards a common model of what we can call the ‘science of embodied intelligent/cognitive agents’. This book is interesting for an interdisciplinary community of researchers, technologists and entrepreneurs working at the frontiers of robotics and AI, neuroscience and general life and brain sciences.

Elena Messina

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