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Performance Metrics for Intelligent Systems (PerMIS)

Performance Metrics for Intelligent Systems (PerMIS)

The PerMIS series, started in 2000, is aimed towards defining measures and methodologies of evaluating performance of intelligent systems.The workshop has proved to be an excellent forum for discussions and partnerships, dissemination of ideas, and future collaborations in an informal setting. Attendees include researchers, graduate students, practitioners from industry, academia, and government agencies.

The workshop focuses on applications of performance measures to practical problems in commercial, industrial, homeland security, and military applications. Topic areas include, but are not limited to:

  • Defining and measuring aspects of a system:
    • The level of autonomy
    • Human-robot interaction
    • Collaboration
  • Evaluating components within intelligent systems
    • Sensing and perception
    • Knowledge representation, world models, ontologies
    • Planning and control
    • Learning and adapting
    • Reasoning
  • Infrastructural support for performance evaluation:
    • Testbeds and competitions for intercomparisons
    • Instrumentation and other measurement tools
    • Simulation and modeling support
  • Technology readiness measures for intelligent systems
  • Applied performance measures in various domains, e.g.,
    • Intelligent transportation systems
    • Emergency response robots (search and rescue, bomb disposal)
    • Homeland security systems
    • De-mining robots
    • Defense robotics
    • Hazardous environments (e.g., nuclear remediation)
    • Industrial and manufacturing systems
    • Space/Aerial robotics
    • Medical Robotics & Assistive devices

Selected papers from the past workshops have been published as special issues with the Journal of Integrated Computer-Aided Engineering (PerMIS'04) and the Journal of Field Robotics (PerMIS'06). The Proceedings of PerMIS are indexed by INSPEC, Compendex, ACM's Digital Library, and are released as a NIST Special Publication.

Created November 8, 2010, Updated September 21, 2016