Many animal swarms, Shklarsh explains, can be harmed by "erroneous positive feedback," a common side effect of navigating complex terrains. This occurs when a subgroup of the swarm, based on wrong information, leads the entire group in the wrong direction. But bacteria communicate differently, through molecular, chemical and mechanical means, and can avoid this pitfall.
Based on confidence in their own information and decisions, "bacteria can adjust their interactions with their peers," Prof. Ben-Jacob says. "When an individual bacterium finds a more beneficial path, it pays less attention to the signals from the other cells. But at other times, upon encountering challenging paths, the individual cell will increase its interaction with the other cells and learn from its peers. Since each of the cells adopts the same strategy, the group as a whole is able to find an optimal trajectory in an extremely complex terrain."
Benefitting from short-term memory
In the computer model developed by the TAU researchers, bacteria decreased their peers' influence while navigating in a beneficial direction, but listened to each other when they sensed they were failing. This is not only a superior way to operate, but a simple one as well. Such a model shows how a swarm can perform optimally with only simple computational abilities and short term memory, says Shklarsh, It's also a principle that can be used to design new and more efficient technologies.
Robots are often required to navigate complex environments, such as terrains in space, deep in the sea, or the online world, and communicate their findings among themselves. Currently, this is based on complex algorithms and data structures that use a great deal of computer resources. Understanding the secrets of bacteria swarms, Shklarsh concludes, can provide crucial hints towards the design of new generation robots that are programm
|Contact: George Hunka|
American Friends of Tel Aviv University