Artificial life concepts [i]
(Click to play gif)
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:
- More interesting environment features.
- Physical traits beyond the decision networks and lifespan.
- A genetic algorithm for generating new agents.
- Faster pseudo-random and pseud0-gaussian number generators, with minimal flops.
- Heritage records to determine which founding organisms were most successful.
- Multiple antagonizing colonies.
- UI to allow realtime environment manipulation.
Labels: animation, ann, genetic programming, life system, neural network, simulation, swarm
posted by Chris at 9:35 PM
3 Comments:
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.
Au contraire, this is about creating life, work is about destroying it.
Can we do these olympics Billy Madison style? I have 'My wife is a dirty tramp' on lock down.
Are you calling my wife a tramp? She is going to cut you.
See you at Toluca Lake.
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