Biological arrow of time: Emergence of tangled information hierarchies and self-modelling dynamics
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
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2024
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| _version_ | 1866909319171145728 |
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| author | Prokopenko, Mikhail Davies, Paul C. W. Harré, Michael Heisler, Marcus Kuncic, Zdenka Lewis, Geraint F. Livson, Ori Lizier, Joseph T. Rosas, Fernando E. |
| author_facet | Prokopenko, Mikhail Davies, Paul C. W. Harré, Michael Heisler, Marcus Kuncic, Zdenka Lewis, Geraint F. Livson, Ori Lizier, Joseph T. Rosas, Fernando E. |
| contents | We study open-ended evolution by focusing on computational and information-processing dynamics underlying major evolutionary transitions. In doing so, we consider biological organisms as hierarchical dynamical systems that generate regularities in their phase-spaces through interactions with their environment. These emergent information patterns can then be encoded within the organism's components, leading to self-modelling "tangled hierarchies". Our main conjecture is that when macro-scale patterns are encoded within micro-scale components, it creates fundamental tensions (computational inconsistencies) between what is encodable at a particular evolutionary stage and what is potentially realisable in the environment. A resolution of these tensions triggers an evolutionary transition which expands the problem-space, at the cost of generating new tensions in the expanded space, in a continual process. We argue that biological complexification can be interpreted computation-theoretically, within the Gödel--Turing--Post recursion-theoretic framework, as open-ended generation of computational novelty. In general, this process can be viewed as a meta-simulation performed by higher-order systems that successively simulate the computation carried out by lower-order systems. This computation-theoretic argument provides a basis for hypothesising the biological arrow of time. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_12029 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Biological arrow of time: Emergence of tangled information hierarchies and self-modelling dynamics Prokopenko, Mikhail Davies, Paul C. W. Harré, Michael Heisler, Marcus Kuncic, Zdenka Lewis, Geraint F. Livson, Ori Lizier, Joseph T. Rosas, Fernando E. Populations and Evolution Formal Languages and Automata Theory Logic in Computer Science Adaptation and Self-Organizing Systems Cellular Automata and Lattice Gases 03Dxx, 68Qxx, 92Dxx, 37N25 F.1.1 We study open-ended evolution by focusing on computational and information-processing dynamics underlying major evolutionary transitions. In doing so, we consider biological organisms as hierarchical dynamical systems that generate regularities in their phase-spaces through interactions with their environment. These emergent information patterns can then be encoded within the organism's components, leading to self-modelling "tangled hierarchies". Our main conjecture is that when macro-scale patterns are encoded within micro-scale components, it creates fundamental tensions (computational inconsistencies) between what is encodable at a particular evolutionary stage and what is potentially realisable in the environment. A resolution of these tensions triggers an evolutionary transition which expands the problem-space, at the cost of generating new tensions in the expanded space, in a continual process. We argue that biological complexification can be interpreted computation-theoretically, within the Gödel--Turing--Post recursion-theoretic framework, as open-ended generation of computational novelty. In general, this process can be viewed as a meta-simulation performed by higher-order systems that successively simulate the computation carried out by lower-order systems. This computation-theoretic argument provides a basis for hypothesising the biological arrow of time. |
| title | Biological arrow of time: Emergence of tangled information hierarchies and self-modelling dynamics |
| topic | Populations and Evolution Formal Languages and Automata Theory Logic in Computer Science Adaptation and Self-Organizing Systems Cellular Automata and Lattice Gases 03Dxx, 68Qxx, 92Dxx, 37N25 F.1.1 |
| url | https://arxiv.org/abs/2409.12029 |