Thermodynamics theories of life can be viewed as a generalization of Darwinism, though in my opinion the abstraction ends up being looser/less productive, and I think it’s more fruitful just to talk in evolutionary terms directly.
I understand how that is generally the case, especially when considering evolutionary systems’ properties. My underlying reason for developing this is that I predict using ML methods on entropy-based descriptions of chaos in NNs will be easier than looking at pure utility functions when it comes to power-seeking.
I imagine that there is a lot more work on existing methods for measuring causal effects and entropy descriptions of the internal dynamics of a system.
I will give an example as the above seems like I’m saying “emergence” as an answer to why consciousness exists, it’s non-specific.
If I’m looking at how deception will develop inside an agent, I can think of putting internal agents or shards against each other in some evolutionary tournament. I don’t know how to set up an arbitrary utility for these shards, so I don’t know how to use the evolutionary theory here. I do know how to set up a potential space of the deception system landscape based on a linear space of the significant predictive variables. I can then look at how much each shard is affecting the predictive variables and then get a prediction of what shard/inner agent will dominate the deception system through the level of power-seeking it has.
Now I’m uncertain whether I would need to care about the free energy minimisation part of it or not. Still, it seems to me that it is more useful to describe power-seeking and what shard/inner agent ends up on top in terms of information entropy. (I might be wrong and if so I would be happy to be told so.)
Thermodynamics theories of life can be viewed as a generalization of Darwinism, though in my opinion the abstraction ends up being looser/less productive, and I think it’s more fruitful just to talk in evolutionary terms directly.
You might find these useful:
God’s Utility Function
A New Physics Theory of Life
Entropy and Life (Wikipedia)
AI and Evolution
I understand how that is generally the case, especially when considering evolutionary systems’ properties. My underlying reason for developing this is that I predict using ML methods on entropy-based descriptions of chaos in NNs will be easier than looking at pure utility functions when it comes to power-seeking.
I imagine that there is a lot more work on existing methods for measuring causal effects and entropy descriptions of the internal dynamics of a system.
I will give an example as the above seems like I’m saying “emergence” as an answer to why consciousness exists, it’s non-specific.
If I’m looking at how deception will develop inside an agent, I can think of putting internal agents or shards against each other in some evolutionary tournament. I don’t know how to set up an arbitrary utility for these shards, so I don’t know how to use the evolutionary theory here. I do know how to set up a potential space of the deception system landscape based on a linear space of the significant predictive variables. I can then look at how much each shard is affecting the predictive variables and then get a prediction of what shard/inner agent will dominate the deception system through the level of power-seeking it has.
Now I’m uncertain whether I would need to care about the free energy minimisation part of it or not. Still, it seems to me that it is more useful to describe power-seeking and what shard/inner agent ends up on top in terms of information entropy. (I might be wrong and if so I would be happy to be told so.)