群れを導くための創発的戦略
Emergent Strategies for Shepherding a Flock
羊飼いが群れを目標へ導く最適な動きをモデル化し、群れの規模と速度に応じて「集める」「追う」「内から導く」の3つの戦略が自然に現れることを示した。
著者: Aditya Ranganathan, Dabao Guo, Alexander Heyde, Anupam Gupta, L. Mahadevan
分類: cond-mat.soft, cs.RO, physics.soc-ph
原文アブストラクト
We investigate how a shepherd should move to effectively herd a flock towards a target. Using an agent-based (ABM) and a coarse-grained (ODE) model for the flock, we pose and solve for the optimal strategy of a shepherd that must keep the flock cohesive and coerce it towards a target. Three distinct strategies emerge naturally as a function of the scaled herd size {and} the scaled shepherd speed: (i) mustering, where the shepherd circles the herd to ensure compactness, (ii) droving, where the shepherd chases the herd in a desired direction while sweeping back and forth, and (iii) driving, where the flock surrounds a shepherd that drives it from within. A minimal dynamical model for the size, shape, and position of the herd captures the effective behavior of the ABM and further allows us to characterize the different herding strategies in terms of the behavior of the shepherd that librates (mustering), oscillates (droving), or moves steadily (driving).
