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A Robot Learns To Fly
jerkychew writes: "For those of you that read my last post about the robot escaping its captors, there's more news regarding robots and AI. According to this Reuters article, scientists in Sweden created a robot that essentially 'learned to fly' in just three hours. The robot had no preprogrammed instructions on how to achieve lift, it had to deduce everything through trial and error. Very interesting stuff."
Not only do we have to watch out for bird crap raining down on us, we now have robot excrement to worry about as well.
~~~~~~~~~ "I must create my own system, or be enslav'd by another man's." William Blake, Jerusalem.
The fact that it "cheats" somehow restores my faith in robotkind....
-ajb
A robot has taught itself the principles of flying -- learning in just three hours what evolution took millions of years to achieve
Well. Assuming the birds were TRYING to fly, knew what lift was, and already had the equipment (i.e. wings) to achieve this.
This brings an image of stupid birds sitting around flapping randomly thinking "FUCK - I'm SURE this should fucking WORK! - Bastards - OOps, I just fell over to the left - does that mean my right wing was flapped right???? - Hey - John! WHAT DID I DO THEN????"
Especially tried to cheat by standing on it's wingtips or similar. I would like to see something else though. What if we build lots of small generic robots, let's say they have wheels to move around only. The on the floor there could be more components that robots can attach themselves to, like giving them legs, wings, arms, eyes, ears etc., and then give them all different objectives, for example to survive, escape, learn from others, etc. Could be interesting to see if it would evolve into some kind of robot society where they all evolve different abilities and so on.
Will work for bandwidth
Imagine a day where engineers build cool robots, upload the generic learn-to-do-stuff-with-your limbs program, leave it for a week or so to train up and get optimum calibration, then have it copy it's program onto subsequent batches.
I picture a robot aerobics class.. heh. But if anybody asks, I picture a robot boot camp.
My life is one big siesta in which I'm dreaming I wished my life was one big siesta.
LONDON (Reuters) - A robot has taught itself the principles of flying -- learning in just three hours what evolution took millions of years to achieve, according to research by Swedish scientists published on Wednesday.
Ridiculous to compare prebuilt robot to evolution from some dinosaur to flying dinosaur (also known as bird). This really is tabloid headlining at it's purest.
And the robot didn't even fly, just generated some lift!
It's like saying humans can fly, when they generate 1N lift flapping their arms.
But it's great to see how selflearning robots and programs will start evolving now. I quess pretty soon computers and robots will be able to evolve faster on their own than when developed by humans.
Sounds like a neural net with real-time recalibration to me..
Stop the brainwash
Rather than comparing this to millions of years of evolution, perhaps it would be better to compare it to a bird just old enough to physically be able to fly.
The robot was physically equipped with all it needed to 'fly'; it was also equipped with all the wires in the right places. The fundamental difference between robots and living organisms is in the thinking: a newborn bird has to forge new synapses in its brain; this robot was designed with the purpose of 'learning to fly', so was given all the appropriate connections; it is just a matter of working out what sequence of events is required. Robots inherently have some form of co-ordination; birds, on the other hand, just like any other animal, have to develop such skills.
Like car accidents, most hardware problems are due to driver error.
"Hey guys, look! We stood on really tall stilts, does this mean we're flying?"
That would have been something to see.
The robot stands proudly on it's wings, and tells the scientists "Look at me, I generated maximum lift, and I don't have to exert any force at all. Oh, and from here, I can see the mouse is climbing over walls to get to the cheese without going through the maze. You humans are so stupid!"
Whoever stated that signature sizes should be limited to one hundred and twenty characters can just go ahead and kiss my
Cheating was one strategy tried and rejected during the process of artificial evolution -- at one point the robot simply stood on its wing tips and later it climbed up on some objects that had been accidentally left nearby.
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But after three hours the robot discovered a flapping technique
However, the robot could not actually fly because it was too heavy for its electrical motor.
"There's only so much that evolution can do," Bentley said.
Finally we understand the dodo's place in evolution.
**AA: a bunch of mindless jerks who'll be the first against the wall when the revolution comes
Here's what I did to play around with breeding algorithms from small building blocks:
Define a very simple stack-based language. The stack only holds boolean values, and when empty pops and endless supply of "false" values and when full discards pushes. Choose some control flow opcodes:
NOP, SKIP (pop, if true, skip ahead a fixed amount), REPEAT (pop, if true, skip back a fxied amount), NOT, RESET (clear stack, back to beginning)
and some opcodes related to your environment (mine was a rectangular arena):
GO (try to move forward one step, push boolean success), TURN (90 degrees clockwise), LOOK (push boolean "do I see food ahead?"), EAT (try to eat, push boolean success)
Pick a stack size (this has interesting consequences, as some of my organisms learned to count by filling the stack with TRUE values and consuming them until they hit the endless supply of FALSE when empty) and a code size. Force all organisms to end in your RESET op. Generate them randomly and run them in your simulator (I did 20-50 at once letting each one run a few hundred instructions in a row). Evaluate fitness (in my case, how well fed they were) and breed them. You can combine the functions in lots of ways. Randomly choose opcodes (or groups of opcodes) from each, possibly with reordering or shifting. Introduce some mutations.
Once you get something interesting, try to figure out how it works. This can be the hardest part -- my description above produced many variations that were only 8-10 instructions long before an unavoidable RESET opcode, and they could search a grid with obstacles for food!
hardly learning, just a new spin on analysing the effeciency of algorithms
Well, analysing efficiency of algorithms and discarding the bad ones seem pretty much like "learning" to me.
Sure, humans aren't built to work efficiently with algorithms like robots do, but we learn from mistakes which one could call "poor algorithms with an undesired result". Humans don't exactly choose randomly between ways to do things - we perform things the way we suceeded in earlier.
Beware: In C++, your friends can see your privates!
You can consider the poor bot some kind of turkey
Rome taught me patience and assiduous application to detail. Virtues which temper the boldness of great, general views.
"It was amazing," said Dr. Heinrich Hienrichson, "Before I knew it, the robot had stolen my credit card, set up an account on Orbitz and booked two airline tickets to Mexico. Now the robot has escaped and my toaster appears to have gone misisng as well..."
----------------------------------- My Other Sig Is Hilarious -----------------------------------
Likely a similar thing happened with dinosaurs turning into birds. The more webbed ones could jump farther and fall farther without getting hurt, and eventually one of them decided to flap its webs and they became wings. Feathers are just longer, more flexible scales, that make flying even easier.
I do agree that what the robot in the article did was not evolution, it was learning. It wasn't even learning a particularly useful form of 'flying', either; it was attached to vertical poles!
--
Seeing is believing; You wouldn't have seen it if you didn't believe it.
What the researchers did was to build a robot that had wings and motors for manipulating them. These could be controlled by a computer. But instead of writing an explicit program telling the robot how to fly, they got the robot to learn how to fly. They did this using some sort of Genetic Algorithm.
Basically, what a GA does is to generate a large population of possible solutions to the problem, then evaluate how good each one is (i.e. measure the lift each one creates in this example) and then to breed good solutions to create successive generations of possible solutions which are (hopefully) better than the previous generations.
Then, once some criterion is met (for example, once the average fitness of your population doesn't change much for several generations), you then select the best solution found so far as being your answer.
In mathematical terms, GAs are stochastic methods of optimising a function; they are typically used when solving the problem using an analytic method would be problematic (i.e. it would take too long etc.).
So it's not really surprising the robot learned to 'fly' -- the researchers just managed to find an optimal sequence of instructions to send to the wings.
The next step would be to get a robot to learn how to hover without the aid of the stabilising poles; then fly from one location to the other; then fly in a straight line in the presence of varying wind etc.
What the research does do is to lend credence to the argument that insects and birds could have evolved, rather than having been 'designed' by some sort of a God.
"The noble art of losing face will one day save the human race"---Hans Blix