Mankind’s best conceivable worldview is at most a partial picture of the real world, a picture, a representation centered on man. We inevitably see the universe from a human point of view and communicate in terms shaped by the exigencies of human life, in a natural uncertain environment by incomplete knowledge. To grasp a more reliable representation of reality, researchers and scientists need two intelligently articulated hands: both stochastic and combinatorial approaches synergistically articulated by natural coupling. In the past, many attempts to arrive to a system continuum-discrete unified mathematical approach have been proposed, all of them with big operational compromises. All these attempts use a top-down (TD) point-of-view (POV). From a computational perspective, all approaches that use a TD POV allow for starting from an exact global solution panorama of analytic solution families, which, unfortunately, offers a shallow local solution computational precision to real specific needs; in other words, overall system information from global to local POV is not conserved, as misplaced precision leads to information dissipation. On the contrary, to develop antifragile system, we need asymptotic exact global solution panoramas combined to deep local solution computational precision with information conservation. The first attempt to identify basic principles to achieve this goal for scientific application has been developing at Politecnico di Milano since the end of last century. In 2013, the basic principles on computational information conservation theory (CICT), for arbitrary-scale discrete system parameter from basic generator and relation, appeared in literature. A synthetic and effective comparative example from a CICT perspective is presented.

Computational Information Conservation Theory: An Introduction

FIORINI, RODOLFO
2014-01-01

Abstract

Mankind’s best conceivable worldview is at most a partial picture of the real world, a picture, a representation centered on man. We inevitably see the universe from a human point of view and communicate in terms shaped by the exigencies of human life, in a natural uncertain environment by incomplete knowledge. To grasp a more reliable representation of reality, researchers and scientists need two intelligently articulated hands: both stochastic and combinatorial approaches synergistically articulated by natural coupling. In the past, many attempts to arrive to a system continuum-discrete unified mathematical approach have been proposed, all of them with big operational compromises. All these attempts use a top-down (TD) point-of-view (POV). From a computational perspective, all approaches that use a TD POV allow for starting from an exact global solution panorama of analytic solution families, which, unfortunately, offers a shallow local solution computational precision to real specific needs; in other words, overall system information from global to local POV is not conserved, as misplaced precision leads to information dissipation. On the contrary, to develop antifragile system, we need asymptotic exact global solution panoramas combined to deep local solution computational precision with information conservation. The first attempt to identify basic principles to achieve this goal for scientific application has been developing at Politecnico di Milano since the end of last century. In 2013, the basic principles on computational information conservation theory (CICT), for arbitrary-scale discrete system parameter from basic generator and relation, appeared in literature. A synthetic and effective comparative example from a CICT perspective is presented.
2014
Proceedings of the 8th International Conference on Applied Mathematics, Simulation, Modelling (ASM '14)
9789604744053
CICT, information geometry, biological correlates, neurological correlates, natural uncertainty, epistemic uncertainty, entropy, wellbeing, health care quality, resilience, antifragility
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/965080
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