Causational studies of life

Poorly narrated video

A quick glance at AIWorld6

First, we see the pre-life world. Here we're seeding the world with agents that have random brain structures until we stumble upon a combination where an agent is smart enough to grow at least some of the time and replicate at least some of the time.

Here we see the first burst of life. This particular growth did not end up being successful in populating the world, but this is the first one to come close to sustainable life.

Many turns later we see the first evolution of war. Notice the agents in the center are spending a lot of time fighting while many around them are growing or replicating. Their brain-hash color is darker green, which distinguishes them as being related in brain structure and having different brains than the other colors. When all the other agents around this time are replicating some of them are ending up in light-green territory which seems to trigger for the first time some previously unused neural pathway to fight. After this moment, the percentage of time agents spend fighting goes from ~0.05% to 1-3% and the number of agents killed in fighting goes up dramatically, almost as high as those killed by starvation. This demonstrates the moment when these agents evolved the ability to defend their territory.

What is the goal of AIWorld6?

AIWorld6 is a tool used to perform causational studies of life and evolution. For example, a question we might ask is 'does the concept of aging cause a species to survive dynamic weather and environment patters better?'

Using only the tools of correlation, we'd have to look for situations where one part of a species did have aging and another part of that species did not. Or where two similar species demonstrated this difference. And then we'd have to look for times when they handled changing environmental conditions that were the same. And then we'd have to find many such examples that were so similar we could 'control' for every possible variable in order to prove a causational link. In short, correlational studies of this kind are impossible.

AIWorld6 solves that by creating a world where evolution is happening in real time and parameters of the world can be easily changed. In this world, all agents are created with equal bodies: same sensors, same abilities, etc. The only difference is their brains; this focuses all evolutionary changes to be on their intellect. By default all agents have a sparse 2-level NN with up to 1000 connections and no feedback loops (memory).

The combination of a simple world and a simple brain allows the simulation to run fast enough that evolution can happen in real time. Running for 4-hour on a 2-proc laptop yields not only the creation of initial lifeforms intelligent at least enough to replicate and grow, but also their first discovery of being able to attack and specific about *when* to attack so they're not blindly killing their offspring or related neighbors.

Now that the basic world is created and can run, the next steps are:

• Design tests that indicate intelligence. These will be the core measure of whether a species is more or less intelligent than another. (Remember that intelligence is the only factor they compete on so success as a species is equivalent to intelligence.)
• Design several tests, like introducing or removing communication, introducing or removing the ability to attack each other, etc.
• Create a long-running peer-to-peer network of the simulation. Today it runs as a single multi-threaded c program with a python UI. Running a long-duration, multi-machine network will allow us to evolve more intelligent creates for more complex tests in the future.