1. Biological arrow of time: Emergence of tangled information hierarchies and self-modelling dynamics
- Author
-
Prokopenko, Mikhail, Davies, Paul C. W., Harré, Michael, Heisler, Marcus, Kuncic, Zdenka, Lewis, Geraint F., Livson, Ori, Lizier, Joseph T., and Rosas, Fernando E.
- Subjects
Quantitative Biology - Populations and Evolution ,Computer Science - Formal Languages and Automata Theory ,Computer Science - Logic in Computer Science ,Nonlinear Sciences - Adaptation and Self-Organizing Systems ,Nonlinear Sciences - Cellular Automata and Lattice Gases ,03Dxx, 68Qxx, 92Dxx, 37N25 ,F.1.1 - Abstract
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., Comment: 30 pages, 13 figures
- Published
- 2024