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

Nader Chmait
IJCAI 2017 pp. 5171-5172
doi:10.24963/IJCAI.2017/745 /ijcai/2017/chmait2017ijcai-understanding/

Abstract

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.

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Text

Chmait. "Understanding and Measuring Collective Intelligence Across Different Cognitive Systems: An Information-Theoretic Approach." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/745

Markdown

[Chmait. "Understanding and Measuring Collective Intelligence Across Different Cognitive Systems: An Information-Theoretic Approach." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/chmait2017ijcai-understanding/) doi:10.24963/IJCAI.2017/745

BibTeX

@inproceedings{chmait2017ijcai-understanding,
  title     = {{Understanding and Measuring Collective Intelligence Across Different Cognitive Systems: An Information-Theoretic Approach}},
  author    = {Chmait, Nader},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {5171-5172},
  doi       = {10.24963/IJCAI.2017/745},
  url       = {https://mlanthology.org/ijcai/2017/chmait2017ijcai-understanding/}
}