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Measuring machine intelligence for human-machine cooperative systems using intelligence task graph

Hee-Jun Park, Byung Kook Kim, Gae-Young Lim

Year
2003
Citations
11

Abstract

We present a practical and systematic strategy for measuring machine (robot) intelligence. A lot of research related to intelligent control has been carried out, but the subjects of definition and measurement of machine intelligence are not clearly formulated yet. We propose a human-oriented definition of machine intelligence and an intelligence task graph (ITG) as a modeling and analysis tool. By using an ITG, the machine contribution of human-machine cooperative systems is easily separated from the human contribution and directly described as numerical equations. Therefore we conclude that the ITG is very useful for estimating the machine intelligence quotient. This research will help engineers design intelligent robots which support human-friendly interfaces and perform environment controls with high performance.

Keywords

Computer scienceHuman–machine systemHuman intelligenceArtificial intelligenceTask (project management)RobotMachine learningGraphComputational intelligenceQuotient

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