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Functional symmetry and reproducibility of the evolutionary process
1Institute of Biophysics of the Siberian Branch of the Russian Academy of Sciences, Krasnoyarsk, Russia Siberian Federal University, Krasnoyarsk, Russia.
Vavilovskii Zhurnal Genetiki I Selektsii
|May 11, 2026
Summary
Evolutionary processes can yield similar outcomes through different structures, even with specialized constraints. This computer modeling study reveals functional symmetry and multiple evolutionary pathways for recurrent neural networks.
Area of Science:
- Evolutionary biology
- Computational neuroscience
- Artificial intelligence
Background:
- Reproducibility of evolutionary processes is crucial for understanding biological systems.
- Computer modeling offers a feasible approach to study evolutionary outcomes, overcoming limitations of real-world experiments.
- Interpreting complex multilevel models requires simplified, heuristic approaches.
Purpose of the Study:
- To identify common properties of evolving systems using a heuristic model.
- To analyze the reproducibility and stability of evolutionary trajectories.
- To investigate functional symmetry in evolved structures.
Main Methods:
- Utilized a heuristic model where agents are recurrent neural networks (NNMOs) that evolve towards maximum fitness.
- Generated ensembles of NNMO structures performing specific functions through computational experiments.
- Analyzed the distribution of NNMOs in structural space and assessed evolutionary trajectory stability.
Main Results:
- Confirmed functional symmetry in NNMO structures performing the same function.
- Demonstrated that constrained evolution (narrow specialization) leads to similar, but not identical, NNMO structures.
- Showcased that evolutionary change allows for redundant structural complexity, enabling multiple, functionally equivalent outcomes.
Conclusions:
- Evolutionary change inherently allows for diverse structural implementations of the same function.
- Functional equivalence can be achieved through different, yet invariant, NNMO structures.
- The study highlights the potential for multiple evolutionary outcomes due to inherent redundancy in complexity.
Keywords:
reproducibility of the evolutionary processequifinality of evolutionary outcomesfunctional complexityfunctional symmetryheuristic neural network modelMore Related Videos
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