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Comment by patcon | Hacker News Reader

I think it's about trying to minimize entropy (disorder) of the system. Maximum entropy is maximum disorder (which the universe tends toward naturally), such as when the pendulum hangs below the cart without any intervention.

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Why is this down voted? It is correct. The article worded it wrong. A system with lower entropy has more future states than a system with high entropy.

Yeah, I had to parse the article a couple times because the wording is wrong. It seems to me that entropica is trying to minimize the entropy of the system. Life is all about low entropy.

Indeed. I'd say intelligence tries to keep its environment in a state it can predict.

I think the trick to understanding this is that, in order for an intelligent being to maintain it's internal homeostasis, it must (in an entropic sense) really screw up it's surrounding environment. Thus, if you look at the whole system, the intelligent being is maximizing entropy. Phrased another way: Because it wants to maximize it's own homeostasis, it has to work extra hard to achieve this. Work creates entropy when looking outside the whole system, and bam - you have entropy maximization.

I'm not sure I'm right, but this logic works for me...

Research just observes that if you try to keep your environment in the state in which you have maximum number of possible futures you can choose from by acting in specific way, then your behavior leading to this state seems intelligent.

Good one: Ralf Der and colleagues proposed homeokinesis as such a principle in 1999. That turned out not to be enough, because the agent would then have an incentive to move into a corner and just hide. That renders the world very predictable, but clearly not a good strategy on the long run.

So, they generalized the method to find a predictable future, but in very unstable states. Later, Der and Ay generalized this towards maximization of predictive information - for that, it is not sufficient to predict to environment, but there also must be something nontrivial to predict. This gives rise to a number of highly interesting behaviours in many of their scenarios.

So, yes, your idea is a good one...

Well, the abstract of the actual paper (linked up-thread) uses the phrase "entropy maximization". I still don't understand entropy after taking a physics class on it, but I did gather it's more complicated than "order" vs "disorder" in any intuitive sense.

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