FWIW I agree with Buck’s criticisms of the Symmetry Theory of Valence (both content and meta) and also think that some other ideas QRI are interested in are interesting. Our conversation on the road trip was (I think) my introduction to Connectome Specific Harmonic Waves (CSHW), for example, and that seemed promising to think about.
I vaguely recall us managing to operationalize a disagreement, let me see if I can reconstruct it:
A ‘multiple drive’ system, like PCT’s hierarchical control system, has an easy time explaining independent desires and different flavors of discomfort. (If one both has a ‘hunger’ control system and a ‘thirst’ control system, one can easily track whether one is hungry, thirsty, both, or neither.) A ‘single drive’ system, like expected utility theories more generally, has a somewhat more difficult time explaining independent desires and different flavors of discomfort, since you only have the one ‘utilon’ number.
But this is mostly because we’re looking at different parts of the system as the ‘value’. If I have a vector of ‘control errors’, I get the nice multidimensional property. If I have a utility function that’s a function of a vector, the gradient of that function will be a vector that gives me the same nice multidimensional property.
CSHW gives us a way to turn the brain into a graph and then the graph activations into energies in different harmonics. Then we can look at an energy distribution and figure out how consonant or dissonant it is. This gives us the potentially nice property that ‘gradients are easy’, where if ‘perfect harmony’ (= all consonant energy) corresponds to the ‘0 error’ case in PCT, being hungry will look like missing some consonant energy or having some dissonant energy.
Here we get the observational predictions: for PCT, ‘hunger’ and ‘thirst’ and whatever other drives just need to be wire voltages somewhere, but for QRI’s theory as I understand it, they need to be harmonic energies with particular numerical properties (such that they are consonant or dissonant as expected to make STV work out).
Of course, it could be the case that there are localized harmonics in the connectome, such that we get basically the same vector represented in the energy distribution, and don’t have a good way to distinguish between them.
On that note, I remember we also talked about the general difficulty of distinguishing between theories in this space; for example, my current view is that Friston-style predictive coding approaches and PCT-style hierarchical control approaches end up predicting very similar brain architecture, and the difference is ‘what seems natural’ or ‘which underlying theory gets more credit.’ (Is it the case that the brain is trying to be Bayesian, or the brain is trying to be homeostatic, and embedded Bayesianism empirically performs well at that task?) I expect a similar thing could be true here, where whether symmetry is the target or the byproduct is unclear, but in such cases I normally find myself reaching for ‘byproduct’. It’s easy to see how evolution could want to build homeostatic systems, and harder to see how evolution could want to build Bayesian systems; I think a similar story goes through for symmetry and brains.
This makes me more sympathetic to something like “symmetry will turn out to be a marker for something important and good” (like, say, ‘focus’) than something like “symmetry is definitionally what feeling good is.”
I think this is a great description. “What happens if we seek out symmetry gradients in brain networks, but STV isn’t true?” is something we’ve considered, and determining ground-truth is definitely tricky. I refer to this scenario as the “Symmetry Theory of Homeostatic Regulation”—https://opentheory.net/2017/05/why-we-seek-out-pleasure-the-symmetry-theory-of-homeostatic-regulation/ (mostly worth looking at the title image, no need to read the post)
I’m (hopefully) about a week away from releasing an update to some of the things we discussed in Boston, basically a unification of Friston/Carhart-Harris’s work on FEP/REBUS with Atasoy’s work on CSHW—will be glad to get your thoughts when it’s posted.
Oh, an additional detail that I think was part of that conversation: there’s only really one way to have a ‘0-error’ state in a hierarchical controls framework, but there are potentially many consonant energy distributions that are dissonant with each other. Whether or not that’s true, and whether each is individually positive valence, will be interesting to find out.
(If I had to guess, I would guess the different mutually-dissonant internally-consonant distributions correspond to things like ‘moods’, in a way that means they’re not really value but are somewhat close, and also that they exist. The thing that seems vaguely in this style are differing brain waves during different cycles of sleep, but I don’t know if those have clear waking analogs, or what they look like in the CSHW picture.)
FWIW I agree with Buck’s criticisms of the Symmetry Theory of Valence (both content and meta) and also think that some other ideas QRI are interested in are interesting. Our conversation on the road trip was (I think) my introduction to Connectome Specific Harmonic Waves (CSHW), for example, and that seemed promising to think about.
I vaguely recall us managing to operationalize a disagreement, let me see if I can reconstruct it:
Of course, it could be the case that there are localized harmonics in the connectome, such that we get basically the same vector represented in the energy distribution, and don’t have a good way to distinguish between them.
On that note, I remember we also talked about the general difficulty of distinguishing between theories in this space; for example, my current view is that Friston-style predictive coding approaches and PCT-style hierarchical control approaches end up predicting very similar brain architecture, and the difference is ‘what seems natural’ or ‘which underlying theory gets more credit.’ (Is it the case that the brain is trying to be Bayesian, or the brain is trying to be homeostatic, and embedded Bayesianism empirically performs well at that task?) I expect a similar thing could be true here, where whether symmetry is the target or the byproduct is unclear, but in such cases I normally find myself reaching for ‘byproduct’. It’s easy to see how evolution could want to build homeostatic systems, and harder to see how evolution could want to build Bayesian systems; I think a similar story goes through for symmetry and brains.
This makes me more sympathetic to something like “symmetry will turn out to be a marker for something important and good” (like, say, ‘focus’) than something like “symmetry is definitionally what feeling good is.”
I think this is a great description. “What happens if we seek out symmetry gradients in brain networks, but STV isn’t true?” is something we’ve considered, and determining ground-truth is definitely tricky. I refer to this scenario as the “Symmetry Theory of Homeostatic Regulation”—https://opentheory.net/2017/05/why-we-seek-out-pleasure-the-symmetry-theory-of-homeostatic-regulation/ (mostly worth looking at the title image, no need to read the post)
I’m (hopefully) about a week away from releasing an update to some of the things we discussed in Boston, basically a unification of Friston/Carhart-Harris’s work on FEP/REBUS with Atasoy’s work on CSHW—will be glad to get your thoughts when it’s posted.
Oh, an additional detail that I think was part of that conversation: there’s only really one way to have a ‘0-error’ state in a hierarchical controls framework, but there are potentially many consonant energy distributions that are dissonant with each other. Whether or not that’s true, and whether each is individually positive valence, will be interesting to find out.
(If I had to guess, I would guess the different mutually-dissonant internally-consonant distributions correspond to things like ‘moods’, in a way that means they’re not really value but are somewhat close, and also that they exist. The thing that seems vaguely in this style are differing brain waves during different cycles of sleep, but I don’t know if those have clear waking analogs, or what they look like in the CSHW picture.)