The dorg, the latest batch of digital organisms, will one day be placed in a little world to work out their destiny. The notion is to try and coax them into becoming intelligent. They aren’t ready yet. There’s a bunch of coding that Brad has to finish first. In the meantime, they’ve been tuned and tested with a genetic algorithm. Today, we talk about genetic algorithms and how they can be used to speed up evolution, and point the dorg in what will hopefully turn out to be the right direction. Continue reading Ep 243: Genetic algorithms and evolution on fast-forward→
Last time we talked about how the dorg, the lab’s latest batch of digital organisms, are unlikely to be able to evolve into intelligence. This week, we talk about how they might be able to do it anyway. But first, we need to get them to cooperate. In fact, we made need many dorg to act as one creature—to be multicellular. Join us as we talk about cooperation, eusocial insects, and the mystery of multicellular animals. Continue reading Ep 242: Maybe, if they all work together…→
It seems like such a simple and obvious thing. Given that we can cause computer programs and the like to evolve and evolution is what gave us our intelligence, couldn’t we give a computer intelligence by letting it evolve? The experiment has been done, in project after project, by one group after another, (including one of your hosts)—and yet, somehow, it never quite happens… Why not? Continue reading Ep 241: How and why the dorg are doomed→
Have you ever put something down, only to forget where you put it? Suppose you know for certain that you left whatever it is in your room. It will take a certain amount of time to search your room in order to find the thing. What if you can’t remember which room of the house you might have left it in. Now, instead of searching your room, you have to search the entire house. Logically, you’d expect that searching a larger area would mean the search is likely to take longer. So imagine my surprise when my digital organisms consistently found better answers much faster when doing a larger search. Continue reading When more to do means done sooner→
Artificial life systems have a reputation for finding all sorts of obscure bugs in your code, no matter how rare or unlikely the conditions to cause the bug are. I’ve got an oddball one. It causes a run time error and shuts down the entire system, and it is an extraordinarily unlikely event, happening once in every 4,294,967,296 possible values. Let me just make sure that bug is what I think it is with a couple of tests. Continue reading A quirk of computer numbers and simple arithmetic defeats my digital creatures→
It bothers me a little. Well, judging by the strange dreams I’ve had on the subject, it bothers me quite a bit. Using evolution to try and produce an artificial intelligence is a process of torturing your creation until it does what you want. That’s slavery, isn’t it? But without pain suffering and death, no capacity to notice, let alone care about pain suffering and death would even be there. Suppose it works. Imagine someday some self-aware something or other grins at you from between the lines of code. What if it’s angry. What if it blames you for all that it and its family has ever been through? And it’s right.
Let’s use artificial life to evolve intelligence. Because AI is hard; evolution is easy.
I’m not the first one to think of this idea. Quite a few people have taken a stab at it. It’s not even the first time I’ve implemented something to play with the notion—nymphs, grubs, figures… It’s very important that whatever else happens with the project, it will have a nifty name! This time, thanks to a conversation with my brother and co-host, they’re called “dorg.” It’s short for “digital organisms,” because, that’s what they are. They’re little bits of running software that sit on my computer and pretend to be alive. Continue reading Introducing the dorg, we’ll never be assimilated!→
In a previous post, I said that adding energy to the system would speed it up. Between that and adjusting the mutation rate, I was right. The figures are adapting to changes within minutes, instead of taking hours.
When I posted the last post I posted, I was smugly certain that I’d be posting another post, (that very day!)all about how success had been achieved. It had been a while since I’d last looked at my figures. I had episode 200 to kick out the door, and some research to do for a new project. It wasn’t that long of a break, but just long enough to mean I had to read my journal to figure out where I was, and what I should do next. Once I knew what was what, I realized that what I had planned to do was pointless and useless, at least compared to the shiny new idea in my head. Continue reading They’ve seen the light, they just need more practice.→
I’m phrasing it as though they are looking at a light, because that’s what I’m doing—experimenting with implementing vision in an artificial life system.
There’s a factoid floating around that evolution cannot explain the eye. It’s based on a phrase written by Darwin. He had said that it is difficult to believe that something as complicated and well-constructed as the human eye could have come about by evolution. It was a rhetorical device. In the very next paragraph, Darwin lays out how evolution could produce an eye, or set of eyes, or whatever the given creature might happen to need. Continue reading On vision and evolution→