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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2311.17403 |
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| _version_ | 1866912195076423680 |
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| author | Li, Johnny Jingze Guerra, Sebastian Prado Basu, Kalyan Silva, Gabriel A. |
| author_facet | Li, Johnny Jingze Guerra, Sebastian Prado Basu, Kalyan Silva, Gabriel A. |
| contents | Emergent effect is crucial to understanding the properties of complex systems that do not appear in their basic units, but there has been a lack of theories to measure and understand its mechanisms. In this paper, we consider emergence as a kind of structural nonlinearity, discuss a framework based on homological algebra that encodes emergence as the mathematical structure of cohomologies, and then apply it to network models to develop a computational measure of emergence. This framework ties the potential for emergent effects of a system to its network topology and local structures, paving the way to predict and understand the cause of emergent effects. We show in our numerical experiment that our measure of emergence correlates with the existing information-theoretic measure of emergence. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_17403 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A Categorical Framework for Quantifying Emergent Effects in Network Topology Li, Johnny Jingze Guerra, Sebastian Prado Basu, Kalyan Silva, Gabriel A. Adaptation and Self-Organizing Systems Category Theory Emergent effect is crucial to understanding the properties of complex systems that do not appear in their basic units, but there has been a lack of theories to measure and understand its mechanisms. In this paper, we consider emergence as a kind of structural nonlinearity, discuss a framework based on homological algebra that encodes emergence as the mathematical structure of cohomologies, and then apply it to network models to develop a computational measure of emergence. This framework ties the potential for emergent effects of a system to its network topology and local structures, paving the way to predict and understand the cause of emergent effects. We show in our numerical experiment that our measure of emergence correlates with the existing information-theoretic measure of emergence. |
| title | A Categorical Framework for Quantifying Emergent Effects in Network Topology |
| topic | Adaptation and Self-Organizing Systems Category Theory |
| url | https://arxiv.org/abs/2311.17403 |