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Simple circuits can create complex behaviors

https://aatishb.com/myriad/lets-build-a-brain/
The ancestor is not Braitenberg. It's Grey Walter's turtles.

In 1948, W. Grey Walter built two simple robots that could sense light and touch.[1] Much complex behavior emerged. That's where this idea started.

Watch the video.[2] It's very impressive for 1948 and tube technology. If you've seen an original Roomba, you've seen a similar level of intelligence. Rod Brooks went down this road. But it didn't go very far. There are severe limits to purely reactive robotics. It doesn't work well for anything that moves fast enough that inertia matters.

[1] https://en.wikipedia.org/wiki/Elmer_and_Elsie_(robots)

[2] https://www.youtube.com/watch?v=lLULRlmXkKo

It’s very odd that Braitenberg didn’t cite Walter’s precedent in ‘Vehicles’. He very likely knew about Walter, Ashby’s homeostat, etc, and used the cybernetics terminology in some of his work.

Fun historical note: the linked newsreel film was known about but unseen for a long time, then found by Owen Holland in the BBC Bristol archive around 1999. Either Owen or I sent it to Rod, to great enjoyment.

Film includes operator-moves-trashcan-with-foot, a staple of mobile robot clips ever since.

See also: https://cyberneticzoo.com/cyberneticanimals/1969-the-logo-tu... In my gifted & talented class in the 80's we were introduced to computers and I remember seeing the picture of "Irving" and thinking "Wow, I should learn LOGO to program robots when I grow up" (unfortunately, recursion scared me so I switched to BASIC and later assembly).
Thank you - also came to comment on Elmer and Elise being the precursor long ago.

Walter himself mentioned the perceived complexity of a simple system to the observer, stating it "might be accepted as evidence of some degree of self-awareness."

Grey Walter also wrote The Living Brain in 1953. It's a fascinating window into the state of brain science and robotics around that time.
The Soviets allegedly used the same principle to make cheap single sensor missile seeker heads.
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Came here to say this and delighted to see it!
> If you saw creatures behaving like this in the wild, you might attribute some rudimentary intelligence to them.

> But we’ve just shown you how this apparent intelligence arises from the bottom up, with just four neurons and two connections. There’s no magic here. In this view, behavior emerges from neural circuits.

Isn't the conclusion here that very simple behaviors like the sparks are intelligent? I would say even a single neuron has some tiny amount of intelligence, and what the author means by "no magic" and "emergent behavior" is just a different perspective that minimizes it.

Intelligence is an arbitrary term humans assign to stuff subjectively.

Take out the "human" and it's all just algos on a scale of complexity.

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Imo most people have to do this to protect themselves from the actual (correct) implications of it, which would be that we're constantly abusing and murdering intelligent beings (and not just animals).

It seems like no one stops to ask, "isn't it kind of bad that we're developing this system of machine intelligence to be our code-writing slaves, without ever really interrogating the ethics? Maybe we don't actually understand how our own brains function well enough to assert it's not similar (especially as language goes) to these kind of weighted association graphs?"

Or even the "well we made it, so it's ours" responses, which we sort of answered a long time ago when we decided kids aren't property, but I digress...

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Check out Valentino Braitenberg's vehicles. It's one of my favourite books ever.
A K Dewdney did a quick sketch of the early chapters of Braitenberg’s book in his Computer Recreations column in _Scientific American_ in the late 1980s.
Came here to mentioned this book. I read it many years back. Wonderful!
I came here to mention that book.
Growing up I tinkered with BEAM robotics. It's a philosophy of design that begins with these types of very simple reactive circuits usually from scavenged parts. It's nice to see someone break down the effect of different variables in the design.

https://en.wikipedia.org/wiki/BEAM_robotics

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Reminds me of BIO bugs from when I was a kid

http://solarbotics.net/BIOBugs/default.htm

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Highly recommend the photovore BEAM robot if you’ve got a soldering iron. It requires a small solar cell and a few analog components from online suppliers like Digikey.

https://youtube.com/watch?v=wi2lpRLfsd8

Best thing is, you can physically build this with a few discrete analog components! Search terms: light-bot, or light following robot. You can try to create swarms adding a light to the rear end of your robot
Love the article, I'm jealous of the author's ability to visualize this. I played with this a while ago using small neural networks and state preference to do something similar, the NNs became self tuning PID controllers and the bots could fly around the simulation like hummingbirds. Was pretty neat.
It reminds me of the computer strategy I devised for my Empire game.
A similar mechanism is how lactobacillus actually find food even though their motor propels them in random directions.

They have sensors for the concentration of food and basically stop moving when it's good enough and start when it's low.

Read this and instantly though about Elmer and Elsie, https://en.wikipedia.org/wiki/Elmer_and_Elsie_(robots)
Love this, it was very clear and fun to read with the simulations!
Hey, just read through the interactive blog post and found it really informative and fun! Thanks for sharing, I come from comp sci undergrad background and am trying to learn more about AI/Neuroscience now, and resources like these make it much easier to learn!
The article mentions the book by Valentino Braitenberg as the source of inspiration.

" The sparks that we assembled in this article are based on a series of thought experiments by the neuroscientist Valentino Braitenberg described in his delightfully quirky 1984 book Vehicles: Experiments in Synthetic Psychology."

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> Aatish is a science journalist with a Ph.D. in physics. Previously, he was a graphics editor at The New York Times. Follow Aatish’s work for more visually-immersive interactive explanations about science.

That is excellent work and well demonstrated by the article.

it is not about simple or complex circuit. non-linear process creates complicate behavior. a nonlinear process can be very simple, and the output can be very complicated.
wow very nice article and animation. we can see some behaviors in the wild life. very interesting.