BackgroundTheoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior.Methodology/Principal FindingsWe extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates.Conclusions/SignificanceBased on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior.

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Interpretation of the living organism's ability to utilize noise from engineering point of view may be beneficial for realizing a simple, yet adaptive, robotic system. This paper presents a bacteria-inspired mobile robot, with a 1-DOF motor and a single sensor. Even with such limitations, the underactuated mobile robot is able to navigate toward a gradient-inducing goal in a two-dimensional space by properly utilizing environmental noise that directly affects its motion. The way the robot utilizes this external noise to control its navigation behavior is interpreted based on biological fluctuation: a simple perspective commonly used to describe how living beings utilize internally generated biological noises.

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Living organisms have various kinds of flexibility and robustness which are realized by "yuragi," or biological fluctuations or noises. Bacterial motion is an example of the noise-based motion, since they can move towards higher concentration of some chemical which they prefer although they have only a limited 1 DOF for mobility using that flagella. Bacteria also have only a limited sensory device which cannot detect the spatial gradient of the chemical at a time. The simple strategies that bacteria take to realize chemotaxis are (1) to tumble (or turn) to change orientation randomly being hit by surrounding water molecules with Brownian motion, and (2) to change the frequency of tumbling according to the change overtime of chemical concentration. In this paper, we describe a quite small and simple, 1 DOF swimming robot developed by mimicking the bacterial motion generation mechanism. The robot only has a single motor and a single sensor (a photo detector). However by changing orientation due to various noises which exist in the environment, and by changing the frequency of turning, the robot can approach its target. Experimental results indicate that the robot statistically approaches the target (a light source) in two dimensional space with a 1 DOF actuator, which is impossible for the robot to achieve without the utilization of the noises in the environment.