Conservation of information: A new approach to organizing human-machine-robotic agents under uncertainty

Abstract

For many years, social scientists have struggled to make sense of the shift between individual and group perception, the difference between observation and action, and the meaning of interdependence. Interactions between these factors produce stable worldviews that contain more illusory than actual connections to reality. We attribute these struggles to scientists embedded in the social fabric, the lack of a measurement theory, and the difficulty of testing new theory with human subjects, groups and organizations. Our work includes field research with observations of citizen organizations advising the Department of Energy (DOE) on its environmental cleanup; laboratory simulations of DOE field results; stock market data; and computational modeling (coupled differential equations, control theory, AI, Gaussian distributions, uncertainty models, Fourier transform pairs, continuous and discrete wavelets). Results from laboratory experiments and stock markets agree with our theory, but many questions remain, forming a high-risk research plan. Our objective is to incorporate interdependent uncertainty into computational intelligence to better instantiate autonomy or decentralized control for mixed human-machine systems. © Springer-Verlag Berlin Heidelberg 2009.