Generating consciousness

One week ago I wrote this post about an insight on what could "consciousness" be like, and I imagined it as something not-so hard to gasp as we always thought. Today I come back with a "pseudo-code" version of it on my mind.

Those new ideas have come along with an effort in our company to port the fractal algorithm into a distributed, highly scalable architecture. A work in progress that is already producing a great speed-up in our tests.

This new architecture allows me to play with big groups of fractals diseminated over a network of PCs, all doing the same decision work in paralell, to later join all their findings and take a "collegiated" decision.

More interestingly, I can now "pack" some fractals to work as one big fractal and replicate it endlessly to build a tree of cooperating fractals as a nice way to distribute work over the PCs on the network.

But how to arrange them to distribute the work even more efficiently? By building it as a "fractal of fractals", a tree of fractals whose structure evolves dynamically as you use it, to finally form a nice tree-like fractal that adapts its form to live in the environment you gave to it.



This new bigger structure, even when used as a static tree-like graph (easier to build on real life PCs) has the power of generating not only intelligence, but consciousness.

To understand wath this consciousness is, we need to zoom this big fractal tree-like structure from a detailed close-up up to the bigger picture.

At a microscope level, the fractal is made up of "states" of the system. A "future" the agent is imagining when thinking is just a possible future state that we make evolve in time to form the fractal structure, but the very tip of this future is just an state, a "position" of our agent.

This initial node of the fractal only knows how to simulate itself to tell us where the agent will be after a little time step pass. If you should calculate this evolution using physics, you should find the feasible change in the state that would make the entropy (of the whole system, the universe) grow at a higher speed (if the 2nd law of thermodynamics is to be assumed). You could think of it as a decision problem: the system have to decide where to go in order to maximize the entropy of the universe.

Now we have a "small" fractal as the one I use for intelligence: a tree-like structure that evolves in time, having on each of its tips -final nodes- a feasible future state.

The effect of this new structure is quite similar to the one seen before: it aims to maximize an entropy again, but calculated after a time horizon, and by doing so, instead of having a "physically correct behaviour", we get an "intelligent behaviour". Kind of magic.

But this fractal is goal-less so it can only generate the simpliest form of intelligence: the "Common sense". To make it trully intelligent, you need to add a goal and modify the entropy formula to take it into account (basically by tampering with the ergodic principle a little).

As far as you only supply one goal, the fractal can add it to the entropy formula and generate an intelligent behaviour in the agent aimed to try to full-fill your (his?) goal.

That is really *all* an intelligence can make at this level: maximize one goal intelligently in a really generic way.

But wait, in my code and videos I manage to make the agents to follow a set of simultaneous -and conflicting- goals, like keep energy high, keep health high, get the rocks into the cave, etc. How?

Well, I just add them together into a single super-goal and ask the AI to follow only this one. Easy trick.

The problem here is that the mix of goals is made up by apply a well-choosen relative strength for each of the goals. May be I need to set them to 90% important for "keep energy high" and only 10% for the health and nothing for the rest in order to survive on hostile environments, as when the food is not so abundant. These vector of weigths for the different goals you have is kind of an art to set manually, as it defines the "personality" of the agent, and you really need a brave agent to survive in some environments, while a gentle one may work better in a more kind environmet.

I tried many times to automatically adjust those coefs by using the fractal I had, but finally I understood that this fractal could never achive this. Anyhow, I added a "master volume" so I could modify how "temperamental" was the agent (as opposed to "common sense" only, that occurs at volume level zero), the "risk control" module, a nice heuristic that prevent the AI to forget about safety and just go straight into the food.

But if now zoom out again and watch the full fractal, a "fractal of fractals of future states", you would see again a tree-like structure like before, but now nodes seems bigger as there is a whole fractal of futures inside.

Now comes the magic: each node of this super-fractal represent a whole previous fractal, even with its own values for the goal strenghts if I wish... so I can "play" with slightly different personalities -adding noise into the initial goal mix- and compare the resulting small-fractals produced after a decision is beign made.

To compare between to fractals I need a new super-goal that will signal the best fractal gowth among all the fractals that forms oure super-fractal, and this goal is aimed to maximize how "beautifull" the fractal is... yes, it sounds crazy, but it is the way I do it manually: try some goal strengths, record a small video, repeat with another goal mix, compare videos... the right choice always produce the most pleasant tree structure, one that seems more "alive" and fresch than the others.

I call this the "leafy coficient" some times, others the "enlightment coeficient" (as it seems to me that thinking with these kind of good-looking fractals is the actual key for enlightment) but the winner was the "cat coefficient", as the more cats a video has, the more visits it receive (quite a silly winner I must admit, but now it is a meme in my head).

Using this "cat coef" as the potential (and euclidean distance over the goal strenght coefs vector) I can make grow this "fractal of fractals" exactly in the same way the small-one did, except that now its pourpouse, apart of taking the best decisions, is also to decide how to change its "personality" to adapt, wich goals should have a the higher priority over time.

So physics was about deciding where will simulation move the agent (physical laws) forming a line in time, intelligence is a one-level fractal that decides where to go -pushing over the degrees of freedom of the system, the "agent's joysticks"- in order to maximize a goal over long periods of time, while consciousness is a two-levels fractal, self-similar with the previous one, that apart from helping take the right decisions, can change the goal-mix in real time to better adapt its personality to the situations and the future to come.

I don't spect to be playing with "consciousness" in the next few months, it is not needed for the problems I am working on, but as the new structure of the code is so perfect for what I need, adding it should be even easy to code, at least using an "static tree" model.