Ucnucs (Unconventional computing / natural computing scientists) party.

As detailed in a paper published this week in *Royal Society Open Science* 
<https://royalsocietypublishing.org/doi/10.1098/rsos.180396>, the amoeba 
used by the researchers is called *Physarum polycephalum*, which has been 
used as a biological computer in several other experiments 
<https://www.newscientist.com/article/dn23713-slime-mould-could-make-memristors-for-biocomputers/>.
 
The reason this amoeba is considered especially useful in biological 
computing 
<https://motherboard.vice.com/en_us/article/jpgdgd/engineers-develop-key-building-block-for-sophisticated-bio-computers>
 is 
because it can extend various regions of its body to find the most 
efficient way to a food source and hates light.
https://motherboard.vice.com/en_us/article/gy7994/an-amoeba-based-computer-calculated-approximate-solutions-to-a-very-hard-math-problem

- pt

On Saturday, December 22, 2018 at 8:09:39 PM UTC-6, Brent wrote:
>
> Bruno should enjoy this. 
>
> Brent 
>
>
> -------- Forwarded Message -------- 
>
> This is a cool bio hack, but is this approach ever going to be faster 
> and/or cheaper than an electronic computer for the same precision of 
> optimization? 
>
>
> https://phys.org/news/2018-12-amoeba-approximate-solutions-np-hard-problem.html
>  
>
> Amoeba finds approximate solutions to NP-hard problem in linear time 
>
> December 20, 2018 by Lisa Zyga, Phys.org 
>
> Researchers have demonstrated that an amoeba--a single-celled organism 
> consisting mostly of gelatinous protoplasm--has unique computing 
> abilities that may one day offer a competitive alternative to the 
> methods used by conventional computers. 
>
> The researchers, led by Masashi Aono at Keio University, assigned an 
> amoeba to solve the Traveling Salesman Problem (TSP). The TSP is an 
> optimization problem in which the goal is to find the shortest route 
> between several cities, so that each city is visited exactly once, and 
> the start and end points are the same. 
>
> https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.180396 
>
> Remarkable problem-solving ability of unicellular amoeboid organism 
> and its mechanism 
>
> Choosing a better move correctly and quickly is a fundamental skill of 
> living organisms that corresponds to solving a computationally 
> demanding problem. A unicellular plasmodium of Physarum polycephalum 
> searches for a solution to the travelling salesman problem (TSP) by 
> changing its shape to minimize the risk of being exposed to aversive 
> light stimuli. In our previous studies, we reported the results on 
> the eight-city TSP solution. In this study, we show that the time 
> taken by plasmodium to find a reasonably high-quality TSP solution 
> grows linearly as the problem size increases from four to eight. 
> Interestingly, the quality of the solution does not degrade despite 
> the explosive expansion of the search space. Formulating a 
> computational model, we show that the linear-time solution can be 
> achieved if the intrinsic dynamics could allocate intracellular 
> resources to grow the plasmodium terminals with a constant rate, even 
> while responding to the stimuli. These results may lead to the 
> development of novel analogue computers enabling approximate solutions 
> of complex optimization problems in linear time. 
>
>
>

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