A slime mold inspired local adaptive mechanism for flow networks

Vidyesh Rao Anisetti; Ananth Kandala; J. M. Schwarz

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arXiv · 2309.16988

A slime mold inspired local adaptive mechanism for flow networks

Vidyesh Rao Anisetti·Ananth Kandala·J. M. Schwarz

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Abstract

In the realm of biological flow networks, the ability to dynamically adjust to varying demands is paramount. Drawing inspiration from the remarkable adaptability of Physarum polycephalum, we present a novel physical mechanism tailored to optimize flow networks. Central to our approach is the principle that each network component -- specifically, the tubes -- harnesses locally available information to collectively minimize a global cost function. Our findings underscore the scalability of this mechanism, making it feasible for larger, more complex networks. We construct a comprehensive phase diagram, pinpointing the specific network parameters under which successful adaptation, or tuning, is realized. There exists a phase boundary in the phase diagram, revealing a distinct satisfiability-unsatisfiability (SAT-UNSAT) phase transition delineating successful and unsuccessful adaptation.

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Vidyesh Rao Anisetti, Ananth Kandala, J. M. Schwarz. 2023-09-29. A slime mold inspired local adaptive mechanism for flow networks. https://arxiv.org/abs/2309.16988

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