[flir]

Completely agree on the importance of the harness.

The problem I see is the same problem Evolutionary Algorithms had: you can generate potential solutions until you run out of cash, but you still need to evalulate those solutions. You need a fitness function, and that means you need to at least know the general shape of the solution. If anyone knows of any work towards more open-ended fitness functions, I'd love to read it.

[ffwd]

Just some speculation, but, I think humans have on the one hand a lot of degrees of freedom in behaviors and thoughts they can do, but at the same time all that freedom is reigned in by our biological needs, like preserving the integrity of our body, but also preserve the integrity of our minds. But this extends further to preserving our surroundings (for our safety, a changing environment brings uncertainty), but also of people we care about and even entire societies that we have. And preserving our future selves through prediction of future environments.

So all that is to say, I'm not sure it is even theoretically possible to create a single algorithm to do open ended search and evaluation. Biology has billions of years of evolution and accumulation, whereas a simple algorithm in a computer, even if smart and connected to the real world, has no such accumulation.

I think humans hit the perfect sweet spot where we have the simplicity of the self preservation instinct, but we have the complexity of the cortex and lots of degrees of freedom because of it, plus on top of that we have a lot of accumulated degrees of freedom in the society and technology and knowledge that have we, which has been built up for thousands of years, all of which we can't just create an algorithm to encapsulate without going through the actual evolution.

And just to make it explicit - a large percentage of what humans think derives from an instinct to preserve the self, the mind, the future and the environment, even if it is very abstract at times. Not absolutely all, but I think a good chunk. And the complexity and degrees of freedom comes from that we have so many neurons in the brain, and a complex body with hands and whatever else that allows a lot of behaviors, as well as a complex environment that is constantly challenging us.

[visarga]

> If anyone knows of any work towards more open-ended fitness functions, I'd love to read it.

There is research in open-ended learning, see "Why Greatness Cannot Be Planned" by Kenneth O. Stanley. The core idea is that in open-ended scenarios you don't know what action was good except in hindsight because your path is deceptive. So the idea is to replace fitness with novelty search which provides more stepping stones towards the goal.

[whiplash451]

The TRM architecture models both the problem and the solution at the same time. You might find it an interesting read.

https://arxiv.org/abs/2510.04871

[piker]

Seems to a layperson like myself that in Math they're using Lean and in programming contexts they're using compilers, such that the models themselves tend towards embedding that determinism "intuitively".