Cost Adjusted MIQ: A New Tool for Measuring Intelligence Value of Systems

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 110)


Most systems that require the operator control can be considered as man–machine cooperative systems in whose functioning, humans, machines and other unintelligent parts play specific roles. Each role has a value. The recently developed machine intelligence quotient (MIQ) measures the contribution provided by the machines to a system. However, for a more practical decision making process, one needs to also consider the cost of improvements. We propose a simple measure of the cost-benefit criterion which enhances the aforementioned concept by adjusting it for the cost, the cost adjusted MIQ (CAMIQ). The method can be especially useful when trying to determine the best solution among several contenders which are similarly valued, but costwise different.


Machine intelligence quotient MIQ Man–machine cooperative system Human–machine cooperative systems Intelligent systems Cost of intelligence 


  1. 1.
    Belli P, Anderson JR, Barnum HN, Dixon JA, Tan J-P (2001) Economic analysis of investment operations. Analytical tools and practical applications. WBI World Bank Report, Washington DCGoogle Scholar
  2. 2.
    Brent RJ (1996) Applied cost-benefit analysis. Edward Elgar, CheltenhamGoogle Scholar
  3. 3.
    Florio M, Vignette S (2003) Cost benefit analysis of infrastructure projects in enlarged EU: an incentive-oriented approach. Paper presented at the fifth European conference on evaluation of the structural funds. “Challenges for Evaluation in an Enlarged Europe”, Budapest, 26/27 JuneGoogle Scholar
  4. 4.
    Flyvbjerg B, Holm MS, Buhl SL (2005) How (In)accurate are demand forecasts in public works projects? J Am Planning Assoc 71(2):131–146CrossRefGoogle Scholar
  5. 5.
    Flyvbjerg B, Holm MS, Buhl SL (2002) Underestimating costs in public works projects Error or Lie? J Am Planning Assoc 68(3):279–295CrossRefGoogle Scholar
  6. 6.
    Bien Z (1998) How to measure the machine intelligence quotient (MIQ): two methods and applications. Proceedings of world automation congress, Anchorage, May 1998Google Scholar
  7. 7.
    Kim S-W, Kim BK (1998) MIQ (Machine Intelligence Quotient) for process control system. Proceedings of world automation congress, Anchorage, May 1998Google Scholar
  8. 8.
    Park H, Kim B, Lim K (2001) Measuring the machine intelligence quotient (MIQ) of human–machine cooperative systems. IEEE Trans Syst man Cybernet 31:89–96CrossRefGoogle Scholar
  9. 9.
    Park H, Kim B, Lim G (1999) Measuring machine intelligence for human–machine cooperative systems using intelligence task graph. Proceedings of the 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 689–694.
  10. 10.
    Ulinwa IC MIQ understanding a machine through multiple perspectives analysis.
  11. 11.
    Anthony A, Jannett TC (2006) Measuring machine intelligence of an agent-based distributed sensor network system. Proceedings of international joint conferences on computer, information, and systems sciences and engineering (CISSE), Dec 2006Google Scholar
  12. 12.
    Ozkul T (2009) Cost-benefit analyses of man–machine cooperative systems by assessment of machine intelligence quotient (MIQ) gain. Proceedings of mechatronics and its applications, 23–26 March 2009Google Scholar
  13. 13.
    Ozkul T, Genc IH (2011) Development of cost adjusted MIQ concept for measuring intelligence value of systems. Lecture notes in engineering and computer science: proceedings of the international multiconference of engineers and computer scientists 2011, IMECS 2011, Hong Kong, 16–18 March 2011, pp 33–37Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentAmerican University of SharjahSharjahUAE
  2. 2.Economics DepartmentAmerican University of SharjahSharjahUAE

Personalised recommendations