Self-learning virtual organisms in a physics simulator: on the optimal resolution of their visual system, the architecture of the nervous system and the computational complexity of the problem
- DOI
- 10.18699/vjgb-25-110
- Published
- 2025-12-12
- Container
- Vavilov Journal of Genetics and Breeding
- Publisher
- Institute of Cytology and Genetics, SB RAS
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.18699/vjgb-25-110,
title = {Self-learning virtual organisms in a physics simulator: on the optimal resolution of their visual system, the architecture of the nervous system and the computational complexity of the problem},
author = {M. S. Zenin and A. P. Devyaterikov and A. Yu. Palyanov},
year = {2025},
journal = {Vavilov Journal of Genetics and Breeding},
doi = {10.18699/vjgb-25-110},
url = {https://doi.org/10.18699/vjgb-25-110}
}RIS
TY - JOUR TI - Self-learning virtual organisms in a physics simulator: on the optimal resolution of their visual system, the architecture of the nervous system and the computational complexity of the problem AU - M. S. Zenin AU - A. P. Devyaterikov AU - A. Yu. Palyanov PY - 2025 JO - Vavilov Journal of Genetics and Breeding DO - 10.18699/vjgb-25-110 UR - https://doi.org/10.18699/vjgb-25-110 ER -
APA
Zenin, M. S., Devyaterikov, A. P., & Palyanov, A. Y. (2025). Self-learning virtual organisms in a physics simulator: on the optimal resolution of their visual system, the architecture of the nervous system and the computational complexity of the problem. Vavilov Journal of Genetics and Breeding. https://doi.org/10.18699/vjgb-25-110
Source records
- crossref · retrieved 2026-09-27T08:28:16.090Z