Much to humans' chagrin, bacteria have superior survival skills. Their decision-making processes and collective behaviors allow them to thrive and even spread efficiently in difficult environments.
Now researchers at Tel Aviv University have developed a computational model that better explains how bacteria move in a swarm and this model can be applied to man-made technologies, including computers, artificial intelligence, and robotics. Ph.D. student Adi Shklarsh with her supervisor Prof. Eshel Ben-Jacob of TAU's Sackler School of Physics and Astronomy, Gil Ariel from Bar Ilan University and Elad Schneidman from the Weizmann Institute of Science has discovered how bacteria collectively gather information about their environment and find an optimal path to growth, even in the most complex terrains.
Studying the principles of bacteria navigation will allow researchers to design a new generation of smart robots that can form intelligent swarms, aid in the development of medical micro-robots used to diagnose or distribute medications in the body, or "de-code" systems used in social networks and throughout the Internet to gather information on consumer behaviors. The research was recently published in PLoS Computational Biology.
A dash of bacterial self-confidence
Bacteria aren't the only organisms that travel in swarms, says Shklarsh. Fish, bees, and birds also exhibit collective navigation. But as simple organisms with less sophisticated receptors, bacteria are not as well-equipped to deal with large amounts of information or "noise" in the complex environments they navigate, such as human tissue. The assumption has been, she says, that bacteria would be at a disadvantage compared to other swarming organisms.
But in a surprising discovery, the researchers found that computationally, bacteria actually have superior survival tactics, finding "food" and avoiding harm more easily than swarms such as amoeba or fish
|Contact: George Hunka|
American Friends of Tel Aviv University