Evolutionary foraging in grids: Intermittent search dynamics emerge in finite, depletable landscapes
Abstract
How search strategies evolve in finite, depletable landscapes remains a question in foraging theory. We study this problem with an evolutionary simulation in which agents forage on a two-dimensional toroidal lattice containing non-renewable resources distributed uniformly or as Lévy dust. Each agent carries a heritable genome encoding step lengths, velocities, and turning angles, and selection acts on a fitness function combining energetic gain, movement cost, and coverage efficiency. By allowing movement traits to evolve without imposing a prescribed power-law step-length distribution, we test whether evolved trajectories are better described by intermittent-search or Lévy-walk dynamics. Our results indicate that evolved search is more consistent with intermittent dynamics than with strict scale-free Lévy motion in the finite depletion-driven landscapes considered here. We characterize the dynamics by fitting second- and fourth-order displacement moments to intermittent-search and Lévy-walk models. While a Lévy-like random walk fits the evolutionary trajectories well (mean adjusted R2 > 0.9 in most tested conditions), intermittent search achieves a closer fit (mean adjusted R2 > 0.99) for all tested resource distributions. This preference holds across the tested grid sizes and resource densities. Five independent evolutionary runs per environment on a 503 x 503 grid at nominal resource density ρ = 0.15 reproduce this preference for the uniform environment and five Lévy-dust environments. Evolution rapidly reshapes the movement genome toward short displacements while retaining a sparse tail of longer relocations, consistent with local exploitation punctuated by occasional transfer. The framework provides a controlled setting for studying how search rules emerge under resource limitation and may inform resource-constrained exploration in autonomous systems.
Related
- The evolutionary accessibility of cultural fitness landscapes
- Stress-recovery dynamics reveal a separatrix in transcriptomic landscapes across organs and aging
- Unraveling Environmental Drivers of Insect Pest Dynamics Across Multiple Landscapes
- Eco-evolutionary dynamics of sexually selected infanticide facilitate species coexistence
- Eco-evolutionary Dynamics of Colonization: When Does Source Selection Matter?
BibTeX
@misc{bhandari2026evolutionary,
title = {{Evolutionary foraging in grids: Intermittent search dynamics emerge in finite, depletable landscapes}},
author = {Shailendra Bhandari and Alex Szorkovszky and Anis Yazidi and Pedro G. Lind},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.39239},
eprint = {2609.39239},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.39239},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Evolutionary foraging in grids: Intermittent search dynamics emerge in finite, depletable landscapes
AU - Shailendra Bhandari
AU - Alex Szorkovszky
AU - Anis Yazidi
AU - Pedro G. Lind
PY - 2026
DA - 2026/09/30
PB - arXiv
DO - 10.48550/arxiv.2609.39239
UR - https://arxiv.org/abs/2609.39239
AB - How search strategies evolve in finite, depletable landscapes remains a question in foraging theory. We study this problem with an evolutionary simulation in which agents forage on a two-dimensional toroidal lattice containing non-renewable resources distributed uniformly or as Lévy dust. Each agent carries a heritable genome encoding step lengths, velocities, and turning angles, and selection acts on a fitness function combining energetic gain, movement cost, and coverage efficiency. By allowing movement traits to evolve without imposing a prescribed power-law step-length distribution, we test whether evolved trajectories are better described by intermittent-search or Lévy-walk dynamics. Our results indicate that evolved search is more consistent with intermittent dynamics than with strict scale-free Lévy motion in the finite depletion-driven landscapes considered here. We characterize the dynamics by fitting second- and fourth-order displacement moments to intermittent-search and Lévy-walk models. While a Lévy-like random walk fits the evolutionary trajectories well (mean adjusted R^2 > 0.9 in most tested conditions), intermittent search achieves a closer fit (mean adjusted R^2 > 0.99) for all tested resource distributions. This preference holds across the tested grid sizes and resource densities. Five independent evolutionary runs per environment on a 503 x 503 grid at nominal resource density ρ = 0.15 reproduce this preference for the uniform environment and five Lévy-dust environments. Evolution rapidly reshapes the movement genome toward short displacements while retaining a sparse tail of longer relocations, consistent with local exploitation punctuated by occasional transfer. The framework provides a controlled setting for studying how search rules emerge under resource limitation and may inform resource-constrained exploration in autonomous systems.
ER -