Unknown, Future, Environment and Systemic - Revision history

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 | 2022.11
-| [[Methodology of Analysis of Unexplained Phenomena|Methodology of Investigation of Unexplained Phenomena]]. To get out of the epistemological quarrels linked to Unexplained Phenomena, presentation of a method of objectification of information which makes it possible to measure the reliability of the explanatory hypotheses envisaged, to evaluate the degree of unknown of a phenomenon and to quantify it. Notions of [[Quantity of Information]], [[Reliability]], [[Strangeness]] and [[Consistency]]. <span class='hashtag'>#UAP Investigation</span>
+| [[Methodology of Analysis of Unexplained Phenomena|Methodology of Investigation of Unexplained Phenomena]]. To get out of the epistemological quarrels linked to Unexplained Phenomena, presentation of a method of objectification of information which makes it possible to measure the reliability of the explanatory hypotheses envisaged, to evaluate the degree of unknown of a phenomenon and to quantify it. Notions of [[Quantity of Information]], [[Reliability]], [[Strangeness]] and [[Consistency]]. [https://zenodo.org/records/18958486 Download slides]. <span class='hashtag'>#Methodology</span> <span class='hashtag'>#UAP Investigation</span>
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 I believe the answer is yes, by structuring it in such a way as to favor the mechanisms of emergence. The approach is twofold: 1/ Granting cells autonomy, by embedding within them their own reproduction rules, rather than having them dictated by the environment. 2/ Allowing cells to transmit their genetic code to their descendants, creating a form of inheritance. By following this approach, one can fully adhere to the original rules of the Game of Life while introducing meaningful variations. Very quickly, intriguing structures begin to emerge, like the one attached here—self-organized, layered, and evolving across different levels of complexity. To bring complexity to life, one must work at the interfaces—those delicate boundaries where scales shift and orders break, fostering cooperation between cells in such a way that new, higher-order structures emerge, more organized than the underlying patterns that preceded them. This [https://github.com/michaelvaillant/genelife little project], developed in JavaScript, is now available on GitHub for exploration.
 Some configurations:
-[https://www.u-sphere.com/projects/genelife2/?seed=96716 Factory], [https://www.u-sphere.com/projects/genelife2/?seed=79273 3 species], [https://www.u-sphere.com/projects/genelife2/?seed=6131 2 species], [https://www.u-sphere.com/projects/genelife2/?seed=56166 Simple lab], [https://www.u-sphere.com/projects/genelife2/?seed=80918 Reconfigurable lab 1],
+[https://www.u-sphere.com/projects/genelife2/?seed=98429 Emerging lab], [https://www.u-sphere.com/projects/genelife2/?seed=96716 Factory], [https://www.u-sphere.com/projects/genelife2/?seed=79273 3 species], [https://www.u-sphere.com/projects/genelife2/?seed=6131 2 species], [https://www.u-sphere.com/projects/genelife2/?seed=56166 Simple lab], [https://www.u-sphere.com/projects/genelife2/?seed=80918 Reconfigurable lab 1],
 [https://www.u-sphere.com/projects/genelife2/?seed=88520 Reconfigurable lab 2]. Find more each time you refresh the page!
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 I believe the answer is yes, by structuring it in such a way as to favor the mechanisms of emergence. The approach is twofold: 1/ Granting cells autonomy, by embedding within them their own reproduction rules, rather than having them dictated by the environment. 2/ Allowing cells to transmit their genetic code to their descendants, creating a form of inheritance. By following this approach, one can fully adhere to the original rules of the Game of Life while introducing meaningful variations. Very quickly, intriguing structures begin to emerge, like the one attached here—self-organized, layered, and evolving across different levels of complexity. To bring complexity to life, one must work at the interfaces—those delicate boundaries where scales shift and orders break, fostering cooperation between cells in such a way that new, higher-order structures emerge, more organized than the underlying patterns that preceded them. This [https://github.com/michaelvaillant/genelife little project], developed in JavaScript, is now available on GitHub for exploration.
 Some configurations:
-[https://www.u-sphere.com/projects/genelife2/?seed=96716|Factory], [https://www.u-sphere.com/projects/genelife2/?seed=79273|3 species], [https://www.u-sphere.com/projects/genelife2/?seed=6131|2 species], [https://www.u-sphere.com/projects/genelife2/?seed=56166|Simple lab], [https://www.u-sphere.com/projects/genelife2/?seed=80918|Reconfigurable lab 1],
+[https://www.u-sphere.com/projects/genelife2/?seed=96716 Factory], [https://www.u-sphere.com/projects/genelife2/?seed=79273 3 species], [https://www.u-sphere.com/projects/genelife2/?seed=6131 2 species], [https://www.u-sphere.com/projects/genelife2/?seed=56166 Simple lab], [https://www.u-sphere.com/projects/genelife2/?seed=80918 Reconfigurable lab 1],
-[https://www.u-sphere.com/projects/genelife2/?seed=88520|Reconfigurable lab 2]. Find more!
+[https://www.u-sphere.com/projects/genelife2/?seed=88520 Reconfigurable lab 2]. Find more each time you refresh the page!
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 | 2024.12
-| [https://www.u-sphere.com/projects/genelife/ A game of life with Genetic Algorithms]. The emergence of complex phenomena within Conway’s Game of Life is nothing short of fascinating. Did you know that, using nothing but the game’s fundamental rules, it is theoretically possible to construct a fully functional computer? It is indeed conceivable, but not something that could happen by mere chance. Left to randomness alone, you would almost certainly never achieve it. So, the real question is: can we subtly guide the game toward such an outcome?
+| [https://www.u-sphere.com/projects/genelife2/ A game of life with Genetic Algorithms]. The emergence of complex phenomena within Conway’s Game of Life is nothing short of fascinating. Did you know that, using nothing but the game’s fundamental rules, it is theoretically possible to construct a fully functional computer? It is indeed conceivable, but not something that could happen by mere chance. Left to randomness alone, you would almost certainly never achieve it. So, the real question is: can we subtly guide the game toward such an outcome?
-I believe the answer is yes, by structuring it in such a way as to favor the mechanisms of emergence. The approach is twofold: 1/ Granting cells autonomy, by embedding within them their own reproduction rules, rather than having them dictated by the environment. 2/ Allowing cells to transmit their genetic code to their descendants, creating a form of inheritance. By following this approach, one can fully adhere to the original rules of the Game of Life while introducing meaningful variations. Very quickly, intriguing structures begin to emerge, like the one attached here—self-organized, layered, and evolving across different levels of complexity. To bring complexity to life, one must work at the interfaces—those delicate boundaries where scales shift and orders break, fostering cooperation between cells in such a way that new, higher-order structures emerge, more organized than the underlying patterns that preceded them. This [https://github.com/michaelvaillant/genelife little project], developed in JavaScript, is now available on GitHub for exploration..
+I believe the answer is yes, by structuring it in such a way as to favor the mechanisms of emergence. The approach is twofold: 1/ Granting cells autonomy, by embedding within them their own reproduction rules, rather than having them dictated by the environment. 2/ Allowing cells to transmit their genetic code to their descendants, creating a form of inheritance. By following this approach, one can fully adhere to the original rules of the Game of Life while introducing meaningful variations. Very quickly, intriguing structures begin to emerge, like the one attached here—self-organized, layered, and evolving across different levels of complexity. To bring complexity to life, one must work at the interfaces—those delicate boundaries where scales shift and orders break, fostering cooperation between cells in such a way that new, higher-order structures emerge, more organized than the underlying patterns that preceded them. This [https://github.com/michaelvaillant/genelife little project], developed in JavaScript, is now available on GitHub for exploration.
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 | 2026.02
 | '''[[Spatial Point Pattern Analysis, Identity-Based Voting and UAPs: The Unknown Connection]]'''. Spatial point pattern modeling of GEIPAN PAN D: nuclear and polluted sites remain significant; adding a territorial proxy based on identity voting (2012) explains part of the residual structure and suggests a parallel sociological dimension (proxy-level, with caveats). <span class='hashtag'>#Methodology</span> <span class='hashtag'>#SpatialStatistics</span> <span class='hashtag'>#UAP</span>
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 | 2025.12

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 | 2025.12
-| '''[https://zenodo.org/records/17888831 Meta-Connective Physics]'''. This paper presents a theoretical framework for the physics of networks and information: a discrete, network-based architecture in which space, time, matter, information, and coherence emerge as angular projections of a single invariant relational tension field Λ₀ and a fundamental angle Θ. Reality is modeled as a lattice of Relational Tension Quanta (RTQs), each carrying a bipolar tension Λ = Λᴾ + iΛᴵ, where Λᴾ encodes metric stiffness (curvature, inertia) and Λᴵ encodes informational coherence (phase alignment). The angular variable Θ distributes Λ₀ between its physical and informational components and generates key observable quantities, including c, ħ, G, and α, as emergent projections rather than primitive constants.
+| '''[https://zenodo.org/records/17891522 Meta-Connective Physics]'''. This paper presents a theoretical framework for the physics of networks and information: a discrete, network-based architecture in which space, time, matter, information, and coherence emerge as angular projections of a single invariant relational tension field Λ₀ and a fundamental angle Θ. Reality is modeled as a lattice of Relational Tension Quanta (RTQs), each carrying a bipolar tension Λ = Λᴾ + iΛᴵ, where Λᴾ encodes metric stiffness (curvature, inertia) and Λᴵ encodes informational coherence (phase alignment). The angular variable Θ distributes Λ₀ between its physical and informational components and generates key observable quantities, including c, ħ, G, and α, as emergent projections rather than primitive constants.
 | 0/5
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