Intermittent search strategies

TL;DR

This review explores the prevalence, modeling, and efficiency of intermittent search strategies across biological scales, highlighting their natural occurrence and potential applications in designing optimized search processes.

Contribution

It provides a comprehensive overview of intermittent search strategies, demonstrating their widespread observation, modeling their efficiency, and proposing broader applications beyond natural systems.

Findings

Intermittent strategies are observed in animals and cellular processes.

Models show intermittent strategies minimize search time.

Potential for designing efficient search algorithms.

Abstract

This review examines intermittent target search strategies, which combine phases of slow motion, allowing the searcher to detect the target, and phases of fast motion during which targets cannot be detected. We first show that intermittent search strategies are actually widely observed at various scales. At the macroscopic scale, this is for example the case of animals looking for food ; at the microscopic scale, intermittent transport patterns are involved in reaction pathway of DNA binding proteins as well as in intracellular transport. Second, we introduce generic stochastic models, which show that intermittent strategies are efficient strategies, which enable to minimize the search time. This suggests that the intrinsic efficiency of intermittent search strategies could justify their frequent observation in nature. Last, beyond these modeling aspects, we propose that intermittent strategies could be used also in a broader context to design and accelerate search processes.