Infopost | 2007.10.15

(May need to click to play)

I'm simulating a collective of independent agents. Each is controlled by a set of neural networks that determine the agent's action. The networks train themselves based on positive and negative action outcomes. Currently they eat, swarm, and reproduce. Above you can see them moving as a collective to consume food (green). Their population (plotted below) fluctuates pretty steadily and you can see the group expand and contract based on environmental stimuli. It's pretty processor-intensive, so I've had to set the environment to support only a few hundred organisms.

The algorithms are still pretty basic, development goals include:


Are you calling my wife a tramp? She is going to cut you.


Au contraire, this is about creating life, work is about destroying it.

This is what you do at work? Now I know who to come to for all the big questions in LIFE. We need to have some sort of mental olympics between a group of us to determine once and for all, the KING and the court jester.


Picking ponies

Naturally I will be indulging my curiosity as to the effectiveness of a good stock market prediction network. It would be a shame not to put money where my mouth is.

Neural networks

I was chatting with Jon about the application of neural networks to stock trading, which is basically a perfect example for explaining the science. It went something like a'this:


A GPT replicant is added to our group chat.