Convergent networked decision-making using group insights

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• 作者：Alexander Raikov
• 关键词：Breakthrough thinking ; Cognitive programming ; Networked decision ; making ; Insight
• 刊名：Complex & Intelligent Systems
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：1
• 期：1-4
• 页码：57-68
• 全文大小：1,253 KB
• 刊物类别：Computational Intelligence; Complexity; Data Structures, Cryptology and Information Theory;
• 刊物主题：Computational Intelligence; Complexity; Data Structures, Cryptology and Information Theory;
• 出版者：Springer Berlin Heidelberg
• ISSN：2198-6053

文摘

In this paper, we propose a mechanism for speeding up networked group expertise (e-expertise) and gaining a collective insight, by structuring the information used in the decision-making process in a special convergent way. We have previously proposed the convergent method for structuring information, which is based on the fundamental principles of control thermodynamics, inverse problems, holistic discourse, cognitive modeling, quantum semantics, and artificial intelligence. This paper presents a further development, which considers breakthrough thinking processes and introduces cognitive programming approaches. We use mappings of unformalized cognitive concepts and their connections into mathematical constructions or sets of objects (documents, messages, comments, etc.) as semantic interpretations of the cognitive model. We applied special structural conditions to the set of semantic interpretations. Our techniques can help groups of experts and decision-makers to create simultaneously non-causal and good decisions. The methods have been implemented as software, the e-expertise system, and have been tested on decision-making processes in e-government conditions.