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Evolutionary simulation reveals intermittent search dynamics in depletable landscapes

By PulseAugur Editorial · [1 sources] ·

A new research paper explores how search strategies evolve in finite, depletable landscapes, using an evolutionary simulation with agents on a grid. The study found that evolved search dynamics are more consistent with intermittent search patterns than strict Lévy-walk dynamics, particularly in finite, depletion-driven environments. The framework developed could inform resource-constrained exploration in autonomous systems. AI

IMPACT This research could inform the development of more efficient exploration strategies for autonomous systems operating in resource-limited environments.

RANK_REASON The cluster contains an academic paper detailing a simulation and its findings. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.NE (Neural & Evolutionary) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Evolutionary simulation reveals intermittent search dynamics in depletable landscapes

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The cluster contains an academic paper detailing a simulation and its findings. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Pedro G. Lind ·

    Evolutionary foraging in grids: Intermittent search dynamics emerge in finite, depletable landscapes

    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 L…

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