Scholars have sliced and diced the terms "ambiguity," "uncertainty," and "ignorance," among others, in a variety of different ways. Oftentimes, the usefulness of these sharp lines isn’t plainly apparent. But one dividing line between types of unknowns, i.e. the distinction between risk and ambiguity, has recently led researchers to fascinating new biological insights. We have something fundamental to learn from the brain and biology about new and much more effective form of computation to develop more effective intelligent system. Our means of new knowledge is reason, the use of observation and logic to learn and prosper. As a matter of fact, in logic, (a) the needs of the individual are what give rise to the need and possibility of value judgments to begin with; and (b) there can be no divide between acting logically and acting human. CICT new awareness of a discrete HG (hyperbolic geometry) subspace (reciprocal space) of coded heterogeneous hyperbolic structures, underlying the familiar Q Euclidean (direct space) surface representation can open the way to holographic information geometry (HIG) to recover lost coherence information in system description. CICT can help us to develop strategies to gather much more reliable experimental information from single experimentation and to keep overall system computational information coherence. This paper is a relevant contribute towards an effective and convenient "Science 2.0" universal computational framework to develop innovative more effective intelligent system and beyond.
Embracing the Unknown in Intelligent Systems
FIORINI, RODOLFO
2016-01-01
Abstract
Scholars have sliced and diced the terms "ambiguity," "uncertainty," and "ignorance," among others, in a variety of different ways. Oftentimes, the usefulness of these sharp lines isn’t plainly apparent. But one dividing line between types of unknowns, i.e. the distinction between risk and ambiguity, has recently led researchers to fascinating new biological insights. We have something fundamental to learn from the brain and biology about new and much more effective form of computation to develop more effective intelligent system. Our means of new knowledge is reason, the use of observation and logic to learn and prosper. As a matter of fact, in logic, (a) the needs of the individual are what give rise to the need and possibility of value judgments to begin with; and (b) there can be no divide between acting logically and acting human. CICT new awareness of a discrete HG (hyperbolic geometry) subspace (reciprocal space) of coded heterogeneous hyperbolic structures, underlying the familiar Q Euclidean (direct space) surface representation can open the way to holographic information geometry (HIG) to recover lost coherence information in system description. CICT can help us to develop strategies to gather much more reliable experimental information from single experimentation and to keep overall system computational information coherence. This paper is a relevant contribute towards an effective and convenient "Science 2.0" universal computational framework to develop innovative more effective intelligent system and beyond.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
