Dedicated to defining measures and methodologies of evaluating performance of intelligent systems

Metrics for Multiagent Systems.- Evaluation Criteria for Human-Automation Performance Metrics.- Performance Evaluation Methods for Assistive Robotic Technology.- Issues in Applying Bio-Inspiration, Cognitive Critical Mass and Developmental-Inspired Principles to Advanced Intelligent Systems.- Evaluating Situation Awareness of Autonomous Systems.- From Simulation to Real Robots with Predictable Results: Methods and Examples.- Cognitive Systems Platforms using Open Source.- Assessing Coordination Demand in Cooperating Robots.- Measurements to Support Performance Evaluation of Wireless Communications in Tunnels for Urban Search and Rescue Robots.- Quantitative Assessment of Robot-Generated Maps.- Mobile Robotic Surveying Performance for Planetary Surface Site Characterization.- Performance Evaluation and Metrics for Perception in Intelligent Manufacturing.- Quantification of Line Tracking Solutions for Automotive Applications.

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.