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Finally done with natural history, today we start talking about the brain. It is extremely complicated. Even a single brain cell, one neuron, is an intricate little machine. Today we take a look at the neuron, and how it sends signals.
I’m sitting on the edge of a binary ocean, casting hyperdimensional nets into the infinite waters of possible programs. My digital creatures, which I call “figures,” will run on my computer for hours, until I finally catch something.
Continue reading It’s like fishing.
Written on Wednesday October3, 2018
Small sample sizes and all those caveats.
I’m tossing out the number of figures being born as a threshold. That will pop out of any of them at any time, and it’s just luck. One of them starts reproducing very quickly, and happens to find a window of relatively few mutation’s, and then skate on through to the finish line.
I retested the first five populations, snagged with a threshold of 100 and 100,000, if memory servs me. Looking at the most mutations given to a population, side by side results, first five and latest five.
Continue reading It bloody well works!
Written on Tuesday October 2, 2018
It seemed like a good idea. Let evolution solve the mutation problem for me. This is procrastination, as what I really need to do next is update the documentation and archive this version. It’s time to clean up the code and concentrate on making the system run faster. Still, I had a few days, and I’d notice that some populations were much more resistant to mutation than others.
Continue reading I was going to say that’s going nowhere, but looking at my notes just now.
Written on Thursday September 27, 2018
mutation each extinction
figures1 skipcom
5.pop average 73
figures just fat
6.pop average 48
x.pop average 460 just fat longest with mu 131616 without only 38453
61.pop keeps doing too well to tell
I was trying to make s.pop into a six figures steady pop size stable population. I wanted to recreate 6.pop whose magic children have done so well that they climb off the measurement scale. I set things up so that s.pop was read from disc and stored in memory. Then, when s.pop died out, she’d be restored from memory rather than from disc. Mutations would happen unless the population was within a certain size range. Once it was all ready and as tested as I was willing to bother with, I let er rip.
Continue reading Think I was trying for the wrong thing.
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For our final episode on the topic of natural history, we take a look at the Pleistocene. This epoch was the most recent ice age, and toward the end of this time, lots of the largest land mammals went extinct, while in the middle of the epoch, humans finally arrived on the scene.
Continue reading Ep 193: The Pleistocene Ice and rat poo
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I managed to talk Phil into co-hosting again, even though he’s far away. Thanks to the internet, we talked about the Pliocene. At the beginning of this time, a nearly dry Mediterranean basin was flooded by the sea, causing a global drop in sea levels. Later, north and south America were connected, allowing plants and animals to travel to new places. This included the largest cat and largest bear ever to roam the Earth.
Continue reading Ep 192: The Pliocene: big bears, big cats, and a really big flood
It was raining. Safe from the downpour, I stood on the porch and enjoyed the weather. Fall is one of my top five favorite seasons, especially if I don’t have to be out in the rain. It was really coming down too, the air filled with the hissing roar of all that water smashing against all that ground. Against the roof, a more percussive pounding, while the bushes and trees in my yard played host to myriad tiny streams and rivulets cascading down their leaves and branches.
Continue reading Perceptions: part II.
Picking it up from yesterday’s entry, I needed to confirm that the quick populations, those that produce new figures quickly, were as fragile as I thought, and for the reasons I thought. I started with m1.
Continue reading The quick are the dead
This might solve everything. I’ll need to do some testing to make sure I’m right, but there’s a beautiful way around the mutation problem.
It’s not the type of mutation; it’s the type of population. We’ve got two main types: the quick and the slow. The quick ones, like m1.pop, do their best to fill up all available space and to make new figures as quickly as possible. The slow ones generally find a particular population size, and stay there, no matter how much more room is available; and they only make new figures slowly. I’ve said several times, and it turns out to be true—speed isn’t everything.
Continue reading Solving the mutation problem