Pursuit and evasion are among the most widespread interactions in which animals engage. Effective evasion may be promoted by adopting various protean behaviors (erratic, unpredictable, and confusing) that may serve to confuse pursuers and increase their reaction time. In this study, pursuers and evaders were modeled as particles moving at a constant speed, with strategy-dependent feedback control rules for direction. The effectiveness of three evasion strategies (pure evasion, random movement and zigzagging) was examined. Different versions of random movement and zigzagging were assessed, using simulations that determined capture time for each version when confronted by a pure pursuit pursuer. Monte Carlo simulations were used in a discrete-time evolutionary game to examine competition among evasion strategies when pitted against pure pursuit players of varying speed and maneuverability. The evolutionary dynamics converge to a pure strategy of zigzag evasion. Directions for future work on evasion are presented.
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