“…noise can enable [organisms] to correctly assess time-variant risk factors in dynamic environments and, as a consequence, to make near-optimal foraging choices…noise may play a crucial role in the decision making of a broad range of self-organized systems”
…a well-attuned level of noise can enable [an organism] to integrate variable risk factors correctly over time. This is not the case if there is little or no noise in the system.
“Self-organized mechanisms are frequently encountered in nature and known to achieve flexible, adaptive control and decision-making. Noise plays a crucial role in such systems: It can enable a self-organized system to reliably adapt to short-term changes in the environment while maintaining a generally stable behavior. This is fundamental in biological systems because they must strike a delicate balance between stable and flexible behavior.”
In the present paper we analyse the role of noise in the decision-making of the true slime mold.
Self-organization enables even simple organisms to solve surprisingly complex tasks, specifically optimization tasks essential for survival. Prominent examples are ant colonies which optimize their foraging choices among multiple food patches taking a variety of criteria into account and slime molds, which optimize path choices even in complex mazes…The question addressed is “can species x efficiently adapt its behavioral patterns to the environmental changes?”
…noise in the decision making process is one of the crucial factors enabling self-organized insect societies to adapt their foraging patterns to changes in the environment…noise is not a disturbance in self-organized systems. On the contrary, noise serves an important functional role.
...the fact that noise enables adaptive decision making is not due to any specific physical details of the ant foraging mechanism. Instead, it arises from very general mathematical properties of the underlying self-organized processes. This suggests that the same should also apply to other similar types of self-organized collective decision making in organisms such as slime molds and bees.
…a well-attuned level of noise can enable the organism to correctly assess a time-variant risk, while the corresponding noise-free system fails to do so. This corroborates that noise plays a crucial functional role in self-organized systems. In biological terms, this is of evolutionary significance.
“…the fact that noise facilitates adaptive decision making is not tied to specific physical details of any particular biological system. Instead, it arises from very general mathematical properties of the underlying self-organized processes.”
Biological systems need to strike a delicate balance between flexible and stable behavior: Stability allows an organism or a group to concentrate its resources and to ignore irrelevant short-term fluctuations in the environment. Yet, adaptation in the case of stronger or more long lasting changes is required. A multi-stable behavior selection mechanism, such as the one analyzed here, can achieve exactly this by exploiting noise. It enables a self-organized system to reliably react to short-term changes in the environment while maintaining a generally stable behavior. The alternative of a control mechanism that follows every change in the environment would potentially be disadvantageous because it leads to unstable behavior.
Mass recruiting ants and slime molds have very little in common biologically and physically. Yet, despite this, the phenomenological mathematical models that describe their behavior selection are very similar when constructed on the right level of observation. The same holds for a variety of other types of self-organized collective decision-making mechanisms in social organisms and human social systems. For example, food source selection and clustering behavior of honey bees, foraging patterns of bacteria, the emergence of fashion trends and the dispersion of innovations all can be and have been described with very similar mathematical models. This explains why some fundamental principles that govern self-organized collective behavior appear to be universal across the range. We may thus expect to also find similar beneficial effects of noise in other instances of self-organized decision making.
Noise has many origins. In any biological system two major influences are fluctuations in the environment and the stochastic nature of the underlying bio-chemical processes themselves. In the behavior of social groups, variations between individuals’ characteristics and the stochastic nature of interactions between group members provide additional sources of noise . Pseudo-randomness in the form of deterministic chaos may also enter into the equation . In fact, no real physical system is noise-free. Usually, however, we expect noise to be a disturbance and to degrade system performance or at best to be irrelevant. It is thus fascinating that evolution seems to have enabled some organisms to make constructive use of noise.