September PerMIS workshop takes measure of intelligent system performance

Intelligent machines of the future will turn custom designs into finished products quickly and efficiently, save lives in catastrophes, and minimize complications caused by surgeries. Researchers involved in advancing artificial intelligence in robots and other systems will gather Sept. 21-23 at the National Institute of Standards and Technology (NIST) in Gaithersburg, Md. to attend the ninth annual Performance Metrics for Intelligent Systems (PerMIS'09) workshop.

Robots with intelligence have to be able to sense, perceive, reason, learn and adapt. Other intelligent systems may have other abilities, for instance, analyzing videotapes to detect suspicious behaviors in individuals within a crowd. The annual PerMIS workshop is the only one of its kind dedicated to defining measures and methodologies to evaluate performance of intelligent systems. PerMIS'09 addresses the question "Does performance measurement accelerate the pace of advancement for intelligent systems?" The workshop focuses on application of performance measures to practical problems in sectors such as industrial, medical, emergency response, transportation, homeland security and defense.

PerMIS is an excellent forum for sharing lessons learned and discussions as well as fostering collaborations between researchers and practitioners from industry, academia and government agencies, according to PerMIS General Chair Elena Messina.

Notable plenary speakers include Tom Mitchell of Carnegie Mellon University whose research in machine learning methods and brain imaging was recently featured on CBS's 60 Minutes, David Bruemmer of Idaho National Laboratory discussing robots and threat detection, Ben Kuipers of University of Michigan, Ann Arbor, describing a cognitive mapper for mobile robots, Paul Cohen of the University of Arizona arguing against sophistication in performance assessments, and Raffaello D'Andrea of ETH Zurich talking about his plan to use hundreds of networked, autonomous mobile robots for order fulfillment in warehousing.

Source: National Institute of Standards and Technology (NIST)