Understanding and Measuring Collective Intelligence Across Different Cognitive Systems: An Information-Theoretic Approach

被引：0

作者：

Chmait, Nader ^{[1
]}

机构：

[1] Monash Univ, Fac Informat Technol, Melbourne, Vic 3800, Australia

来源：

PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2017年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We develop the idea of collective intelligence by analysing a range of factors hindering the effectiveness of interactive cognitive agents. We give insights into how to explore the potential of collectives across different cognitive systems (human, animal and machine) and research areas. The endeavour is to bridge the different research disciplines in which collective intelligence might occur and apply the studies of intelligence in AI to other fields, thereby cross-fertilising diverse areas of study ranging from business and management to social sciences and fundamental biology.

引用

页码：5171 / 5172

页数：2

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