In episode 144, I oh so casually mentioned that I was getting some runtime errors. They don’t happen in every run, but the fact that they happen at all is a problem. My artificial life system will eventually be running for days at a time as I do different experiments, and I can’t have these errors causing my system to halt.
What does one do when one sees output like the following?
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In episode 139 and 142, I talked about some results I’ve been getting with my experiment with artificial life and digital organisms. I had to rework the death object to make sure that one of the little critters would die and make room for others. But does an unusually long-lived creature really inhibit evolution? I found a counter example—Pando, an 80,000-year old quaking aspen clonal colony. Though it was established during the last ice age, the plant and animal life around it has definitely changed and evolved since then, suggesting that in nature, long lived creatures do not keep evolution from happening.
Here’s a link to a 4-minute and 42-second long video about Pando.
Pando, One of the Oldest and Largest Organisms
Here are links to a couple of articles about this venerable organism.
Pando, the Trembling Giant – Richfield, Utah – Atlas Obscura
And here are some links to information about the last ice age, called the “Pleistocene.”
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In the previous episode, I provided a description of “Amoeba.” In this episode I use “Figures,” which is my own experiment with digital organisms and artificial life, to repeat the results of Andy Pargellis’s Amoeba experiment, with a few differences. I also give the most detailed explanation of my subleq based system to date, as I compare and contrast it with Tierra and Amoeba.
Here are links to episodes relevant to today’s episode
Ep 143: Emergent self-replication with Amoeba
Ep 103: Tierra, bits bytes and life
Here’s a blog post that describes what subleq is and how it works.
The prime, and only, directive.
Here’s a video that provides a decent introduction to artificial life and digital organisms.
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Did life come from chaos? If it did, could you get artificial life to do the same thing? As I’m repeating the experiment, with some difference, I thought I’d talk about Amoeba—an artificial life simulation that caused self-replicating bits of software to emerge from randomly generated code. I provide a general overview, and then talk a little bit about how it relates to my project.
Here are links to the previous episodes that relate to today’s episode.
Ep 103: Tierra, bits bytes and life
Here’s a link to an article about Amoeba.
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In episode 139, I talked about unexpected results from my experiment with artificial life and digital organisms. There was a tiny bit of evolution happening with a very tiny population. Today, we take a closer look at what the system was doing.
Here are links to previous episodes relevant to this one.
Ep 103: Tierra, bits bytes and life
Ep 139: de facto fitness functions and unexpected early evolution
Here’s a roughly 28-minute-long video that is a decent introduction to artificial life.
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Not every single-celled life form is microscopic. Some of them can be seen with the naked eye. Some of them are, at least compared to other single-celled creatures, downright gigantic.
Here’s an article about the large amoeba that was found on the bottom of the ocean.
Giant single celled organisms lurk on ocean’s deepest point
Here’s an article about a single celled bit of seaweed that looks like a tiny fern.
Structure of world’s largest single cell is reflected at the molecular level
And here’s a video about why single celled organisms don’t get much larger than the examples in today’s episode.
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As soon as you’ve defined something like Eukaryotes, some exception crops up, and you have to redefine a classification of life. Today, we look at one or two such exceptions, including an animal that doesn’t use oxygen.
Here are links to the episodes referenced in today’s “exciting” episode.
Ep 68: An environmental catastrophe
Here are a couple of articles about the single-celled Eukaryote that has no mitochondria.
Surprise! This eukaryote completely lacks mitochondria
First eukaryotes found without a normal cellular power supply
And here are some articles on the animal that doesn’t use oxygen.
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When people talk about their artificial life computer simulations, they often say that there is no fitness function—no bit of code that decides which bit of software lives, dies, or reproduces. Even if it isn’t happening on purpose, the design of the overall system can still cause a de facto fitness function, and behaviors you didn’t expect, and perhaps, really didn’t want. It has already happened to me and my figures, despite using only a small test population of two or three individuals.
Here’s a link to episode 112, about Polyworld.
Evolving neural networks with polyworld
Here’s a link to a talk about Polyworld. The interesting bit where their de facto fitness function caused problems is at 30 minutes and 25 seconds.
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While researching for these episodes, I’ve also been researching for other reasons, including the experiment which I talk about today. It’s my attempt to use artificial life for artificial intelligence.
Here’s a link to episode 103, which describes Tiera, and gives a good overview of digital organisms and artificial life.
Here’s a link to episode 54, which includes an example of the real-world effects when you’re AI system over fits.
Irrational computers, investing, and racist robots
And here’s a link to the most recent post on my on-going work with digital organisms.
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@seeingwithsound asked me if my lucid dreams are visual, and if so, how vivid or realistic are the experiences. The answer is somewhat interesting, so I went ahead and made an episode out of it.
Here’s a link to the website of the vOICe—a sensory substitution device.
Here’s episode 19, that demonstrates the vOICe.
Here’s a link to an article about which parts of the visual system of the brain are active and inactive during sleep and dreaming.
Inside The Brain Of The REM Sleeper
And just for fun, here’s a link to an article about blindsight.