Information-Driven Order Formation in Natural and Artificial Systems
| dc.contributor.author | Barack Ndenga | |
| dc.date.accessioned | 2025-12-18T00:49:47Z | |
| dc.date.issued | 2025-12-17 | |
| dc.description | This article develops an information-centered framework to explain how order emerges and persists in natural and artificial systems. It argues that informational constraints play a central role in shaping system dynamics by restricting accessible states and counteracting entropic dispersion. By extending traditional thermodynamic perspectives, the work provides a unified interpretation of order formation across physical, biological, and computational systems. The accompanying supplementary material further clarifies the conceptual foundations, mechanisms, and implications of information-driven organization. | |
| dc.description.abstract | The spontaneous formation of order in complex systems remains a central problem across physics, biology, and artificial intelligence. While thermodynamics constrains irreversibility through entropy, it does not fully explain why organized structures emerge, persist, and adapt far from equilibrium. In this article, I develop an information-centered framework in which order formation is driven by informational constraints that channel system dynamics and counteract entropic dispersion. I analyze the mechanisms through which information shapes organization in natural and artificial systems, introduce a unifying interpretation based on organizational efficiency, and demonstrate how this perspective applies across physical, biological, and computational domains. This work provides a coherent theoretical foundation for understanding order as an information-driven phenomenon. Keywords Information-driven organization; order formation; complex systems; entropy; self-organization; biological systems; artificial intelligence; non-equilibrium thermodynamics. | |
| dc.description.provenance | Submitted by Barack Ndenga (ndengabarack@gmail.com) on 2025-12-18T00:49:47Z No. of bitstreams: 2 84th .pdf: 423128 bytes, checksum: efc1f163ed5574b3712e122b2c822dc1 (MD5) license_rdf: 1166 bytes, checksum: d700fae5b268849d8bbda3dffdc09cde (MD5) | en |
| dc.description.provenance | Made available in DSpace on 2025-12-18T00:49:47Z (GMT). No. of bitstreams: 2 84th .pdf: 423128 bytes, checksum: efc1f163ed5574b3712e122b2c822dc1 (MD5) license_rdf: 1166 bytes, checksum: d700fae5b268849d8bbda3dffdc09cde (MD5) Previous issue date: 2025-12-17 | en |
| dc.description.sponsorship | None | |
| dc.identifier.uri | https://africarxiv.ubuntunet.net/handle/1/10647 | |
| dc.language.iso | en | |
| dc.publisher | Publisher | |
| dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | |
| dc.title | Information-Driven Order Formation in Natural and Artificial Systems | |
| dc.type | Article |