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Researchers at the Technische Universitat Wein have created a simulation of a simple worm’s neural network, and have been able to replicate its natural behavior to completely mimic the worm’s natural reflexive behavior. According to the article, using a simple neural network of 300 neurons, the simulation of “the worm can find its way, eat bacteria and react to certain external stimuli. It can, for example, react to a touch on its body. A reflexive response is triggered and the worm squirms away. This behavior is determined by the worm’s nerve cells and the strength of the connections between them. When this simple reflex network is recreated on a computer, the simulated worm reacts in exactly the same way to a virtual stimulation — not because anybody programmed it to do so, but because this kind of behavior is hard-wired in its neural network.” Using the same neural network without adding any additional nerve cells, Mathias Lechner, Radu Grosu, and Ramin Hasani were able to have the nematode simulation learn to balance a pole “just by tuning the strength of the synaptic connections. This basic idea (tuning the connections between nerve cells) is also the characteristic feature of any natural learning process.”

On Wednesday, the the Defense Enterprise Science Initiative, or DESI, announced a competition for basic science grants to build “new paradigms for autonomous flight, with a focus on highly-maneuverable platforms and algorithms for flight control and decision making.”

Biomimetic, or nature-imitating, designs for crawling, slinking and even swimming robots go back decades.

But getting flying machines to mimic nature is a good deal more difficult and more complicated than teaching robots to swim and crawl, which is why even the military’s smallest drones have followed conventional aerodynamic designs.