Biological arrow of time: emergence of tangled information hierarchies and self-modelling dynamics
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 e...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
|
| Series: | Journal of Physics: Complexity |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2632-072X/ad9cdc |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832590538869571584 |
|---|---|
| author | Mikhail Prokopenko Paul C W Davies Michael Harré Marcus G Heisler Zdenka Kuncic Geraint F Lewis Ori Livson Joseph T Lizier Fernando E Rosas |
| author_facet | Mikhail Prokopenko Paul C W Davies Michael Harré Marcus G Heisler Zdenka Kuncic Geraint F Lewis Ori Livson Joseph T Lizier Fernando E Rosas |
| author_sort | Mikhail Prokopenko |
| collection | DOAJ |
| description | 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 | Article |
| id | doaj-art-6b0b3da2510c4f21a264dc04b2a37667 |
| institution | Kabale University |
| issn | 2632-072X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Journal of Physics: Complexity |
| spelling | doaj-art-6b0b3da2510c4f21a264dc04b2a376672025-01-23T12:41:51ZengIOP PublishingJournal of Physics: Complexity2632-072X2025-01-016101500610.1088/2632-072X/ad9cdcBiological arrow of time: emergence of tangled information hierarchies and self-modelling dynamicsMikhail Prokopenko0https://orcid.org/0000-0002-4215-0344Paul C W Davies1Michael Harré2Marcus G Heisler3Zdenka Kuncic4https://orcid.org/0000-0001-6765-3215Geraint F Lewis5https://orcid.org/0000-0003-3081-9319Ori Livson6https://orcid.org/0009-0001-8425-589XJoseph T Lizier7https://orcid.org/0000-0002-9910-8972Fernando E Rosas8The Centre for Complex Systems, University of Sydney , Sydney, NSW 2006, Australia; School of Computer Science, Faculty of Engineering, University of Sydney , Sydney, NSW 2006, AustraliaThe Beyond Center for Fundamental Concepts in Science, Arizona State University , Tempe, AZ 85287–0506, United States of AmericaThe Centre for Complex Systems, University of Sydney , Sydney, NSW 2006, Australia; School of Computer Science, Faculty of Engineering, University of Sydney , Sydney, NSW 2006, AustraliaThe Centre for Complex Systems, University of Sydney , Sydney, NSW 2006, Australia; School of Life and Environmental Sciences, Faculty of Science, University of Sydney , Sydney, NSW 2006, AustraliaThe Centre for Complex Systems, University of Sydney , Sydney, NSW 2006, Australia; School of Physics, Faculty of Science, University of Sydney , Sydney, NSW 2006, Australia; The Charles Perkins Centre, University of Sydney , Sydney, NSW 2006, AustraliaSchool of Physics, Faculty of Science, University of Sydney , Sydney, NSW 2006, AustraliaThe Centre for Complex Systems, University of Sydney , Sydney, NSW 2006, Australia; School of Computer Science, Faculty of Engineering, University of Sydney , Sydney, NSW 2006, AustraliaThe Centre for Complex Systems, University of Sydney , Sydney, NSW 2006, Australia; School of Computer Science, Faculty of Engineering, University of Sydney , Sydney, NSW 2006, AustraliaSussex AI and Centre for Consciousness Science, Department of Informatics, University of Sussex , Brighton BN19RH, United Kingdom; Centre for Psychedelic Research, Department of Brain Science, Imperial College London , London SW72AZ, United Kingdom; Centre for Complexity Science, Imperial College London , London SW72AZ, United Kingdom; Center for Eudaimonia and Human Flourishing, University of Oxford , Oxford OX39BX, United KingdomWe 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.https://doi.org/10.1088/2632-072X/ad9cdctangled hierarchyself-referenceundecidabilityopen-ended complexityevolutionary transition |
| spellingShingle | Mikhail Prokopenko Paul C W Davies Michael Harré Marcus G Heisler Zdenka Kuncic Geraint F Lewis Ori Livson Joseph T Lizier Fernando E Rosas Biological arrow of time: emergence of tangled information hierarchies and self-modelling dynamics Journal of Physics: Complexity tangled hierarchy self-reference undecidability open-ended complexity evolutionary transition |
| title | Biological arrow of time: emergence of tangled information hierarchies and self-modelling dynamics |
| title_full | Biological arrow of time: emergence of tangled information hierarchies and self-modelling dynamics |
| title_fullStr | Biological arrow of time: emergence of tangled information hierarchies and self-modelling dynamics |
| title_full_unstemmed | Biological arrow of time: emergence of tangled information hierarchies and self-modelling dynamics |
| title_short | Biological arrow of time: emergence of tangled information hierarchies and self-modelling dynamics |
| title_sort | biological arrow of time emergence of tangled information hierarchies and self modelling dynamics |
| topic | tangled hierarchy self-reference undecidability open-ended complexity evolutionary transition |
| url | https://doi.org/10.1088/2632-072X/ad9cdc |
| work_keys_str_mv | AT mikhailprokopenko biologicalarrowoftimeemergenceoftangledinformationhierarchiesandselfmodellingdynamics AT paulcwdavies biologicalarrowoftimeemergenceoftangledinformationhierarchiesandselfmodellingdynamics AT michaelharre biologicalarrowoftimeemergenceoftangledinformationhierarchiesandselfmodellingdynamics AT marcusgheisler biologicalarrowoftimeemergenceoftangledinformationhierarchiesandselfmodellingdynamics AT zdenkakuncic biologicalarrowoftimeemergenceoftangledinformationhierarchiesandselfmodellingdynamics AT geraintflewis biologicalarrowoftimeemergenceoftangledinformationhierarchiesandselfmodellingdynamics AT orilivson biologicalarrowoftimeemergenceoftangledinformationhierarchiesandselfmodellingdynamics AT josephtlizier biologicalarrowoftimeemergenceoftangledinformationhierarchiesandselfmodellingdynamics AT fernandoerosas biologicalarrowoftimeemergenceoftangledinformationhierarchiesandselfmodellingdynamics |