PreprintCC BY-NC-ND 4.0arXiv
Noise-robust navigation from an adaptive run-and-tumble policy
Abstract
How do organisms navigate when the signals guiding them are noisy? Variance adaptation, the rescaling of sensitivity to noise, is common in sensory systems, but its role in navigation is unexplored. We introduce a minimal active Brownian particle whose run-and-tumble policy follows from an optimality principle. Variance adaptation emerges as part of this policy. Adaptation keeps chemotactic drift finite as noise grows, while a non-adaptive particle's collapses exponentially. Adaptation also carries a cost, degrading performance in quiet environments and requiring a tuned adaptation sensitivity.
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BibTeX
@misc{datta2026noiserobust,
title = {{Noise-robust navigation from an adaptive run-and-tumble policy}},
author = {Aniruddha Datta and Shiladitya Banerjee},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2608.27751},
eprint = {2608.27751},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.27751},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Noise-robust navigation from an adaptive run-and-tumble policy
AU - Aniruddha Datta
AU - Shiladitya Banerjee
PY - 2026
DA - 2026/08/27
PB - arXiv
DO - 10.48550/arxiv.2608.27751
UR - https://arxiv.org/abs/2608.27751
AB - How do organisms navigate when the signals guiding them are noisy? Variance adaptation, the rescaling of sensitivity to noise, is common in sensory systems, but its role in navigation is unexplored. We introduce a minimal active Brownian particle whose run-and-tumble policy follows from an optimality principle. Variance adaptation emerges as part of this policy. Adaptation keeps chemotactic drift finite as noise grows, while a non-adaptive particle's collapses exponentially. Adaptation also carries a cost, degrading performance in quiet environments and requiring a tuned adaptation sensitivity.
ER -