Biological arrow of time: Emergence of tangled information hierarchies and self-modelling dynamics
<|reference_start|>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 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 G\"odel--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.<|reference_end|>
@article{prokopenko2024biological,
    title={Biological arrow of time: Emergence of tangled information hierarchies
  and self-modelling dynamics},
    author={Mikhail Prokopenko, Paul C. W. Davies, Michael Harr'e, Marcus
  Heisler, Zdenka Kuncic, Geraint F. Lewis, Ori Livson, Joseph T. Lizier,
  Fernando E. Rosas},
    journal={arXiv preprint arXiv:2409.12029},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.12029},
    primaryClass={q-bio.PE cs.FL cs.LO nlin.AO nlin.CG}
}