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A machine-learning software-systems approach to capture social,\n regulatory, governance, and climate problems

2020/02/23 by Christopher A. Tucker, Tucker, Christopher A.
Computer Science · Decision Sciences · Economics, Econometrics and Finance · Engineering · #Artificial Intelligence (cs.AI) #Cognitive Science and Mapping #Complex Systems and Decision Making #Economic Development and Digital Transformation #Economic and Technological Innovation #FOS: Computer and information sciences #Infrastructure Resilience and Vulnerability Analysis

paper · pdf · doi:10.48550/arxiv.2002.11485

openalex publication_date 2020/02/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper will discuss the role of an artificially-intelligent computer\nsystem as critique-based, implicit-organizational, and an inherently necessary\ndevice, deployed in synchrony with parallel governmental policy, as a genuine\nmeans of capturing nation-population complexity in quantitative form, public\ncontentment in societal-cooperative economic groups, regulatory proposition,\nand governance-effectiveness domains. It will discuss a solution involving a\nwell-known algorithm and proffer an improved mechanism for\nknowledge-representation, thereby increasing range of utility, scope of\ninfluence (in terms of differentiating class sectors) and operational\nefficiency. It will finish with a discussion of these and other historical\nimplications.\n

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