I worked on Adobe’s Flash Player team at that time and I remember using your Flash movie as a test case. :)

Do you have some examples of results when running this for a few days?

Or perhaps, 20 years? ;-)

On Firefox here, the "Save Local Population" option seems to crash. Any idea why that might be happening? (Amazing site btw - every time it pops up I end up spending much too long with it).

What would be the consequences of adding a hitbox on the structure (or springs?) as well, as opposed to having it only on the load?

As internet distractions go, the original was one of the most memorable I ever came across. A friend and I used to leave them running over lunch and see who was winning when we got back. Thanks for the fun :-)

I remember running this in the background any time I was in the computer lab at school. Thanks for making this back in the day :).

There were a few genetic algorithm "polygons approximate picture" pages back in that era as well.

Thanks for writing this all those years ago. It made for a fun demonstration when I was learning genetic algos in college.

>Maybe this is just an attribute of genetic algorithms

It happened to crocodiles and it could happen to you too.

In general, one should keep the mutation rate really low to allow the population slowly change over time. High mutation rate will lead to local optima quickly but also very hard to get out. Low mutation rate will require significant more generations but in general result in better adaptation.

Sounds like you're running with a single elite clone. That's a really bad idea in genetic heuristics for exactly the phenomenon you mention.

If you keep going long enough they'll probably turn into crabs.

It seems like more should change than just the shape. I'd wager that a slower car with more power may be less likely to get stuck in ruts. But it seems that the power and speed don't vary, just (barely, after a few generations) the shape.

Edit, I scrolled down and it covers the genome:

• Shape (8 genes, 1 per vertex)

• Wheel size (2 genes, 1 per wheel)

• Wheel position (2 genes, 1 per wheel)

• Wheel density (2 genes, 1 per wheel) darker wheels mean denser wheels

• Chassis density (1 gene) darker body means denser chassis

It basically lands on a two-wheeled medium-bodied shape and doesn't seem to make much progress after that. Power and speed would be interesting variations.

What happens in an evolutionary algorithm depends on what you write it for. This is a fun toy, but what it does specifically is explore a very limited simulation of evolution by natural selection. Metaheuristics aimed at optimization have a lot of techniques aimed at not stalling out on a prematurely converged design, as well as improving other desirable properties of the population, at the expense of any pretense of fidelity to real-world evolution processes.

This is why I said it needed crossover and got downvoted into oblivion :) turns out it at least tries to have crossover, so maybe the genome doesn't translate to crossover doing anything relevant.

I wasn't fooling. Think about it for a second, if your process involves a lot of crossover that means large sections of working genome will be passed on. If the ONLY mechanism for changing anything is mutation, then mostly you're just breaking what works.

That's what you're describing, so I'd look at how the genome is constructed to understand why it's not doing more.

More improvement needs wild environment changes.

> EVerything more or less evolved into a sort of tron-bike shape for most of the runs I tried.

I ran it in the background for a very high mutation rate for a long time and it managed to come up with something very different---a little wheel attached to a big wheel, which bounces around and goes over all the obstacles.

...and apparently all the suspension parameters stripped out for some bizarre reason.

The physics simulation clearly uses inelastic collisions, which is wildly unrealistic and why so many otherwise passable 'cars' don't pass the course. Also seems to use a very low coefficient of friction - most of my cars couldn't make it up a two-segement slope.

... Apparently boxcar2d works perfectly in Ruffle, which the Internet Archive automatically loads :)

https://web.archive.org/web/20240428203838/http://boxcar2d.c...

I knew I had seen something like this over a decade ago!

The Great Filter

Time comes for us all

Just wait a little longer for the flying cars.

The simulation that these cars are driving in has no third dimension for the vehicle to fall over into (or where to put another pair of wheels). So, like a traditional four-wheeled car, these vehicles do not tip over at 0 velocity. I think that property is enough to qualify their behaviour as more similar to four-wheeled cars than motorbikes.