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Thanks, nice work.

The comment: 13 points Hey 02 November 2011 09:01:09AM is maybe something you want to remove.

West and Brown has done some work on this which seemed pretty solid to me when I read it a few months ago. The basic idea is that biological systems are designed in a fractal way which messes up the dimensional analysis.

From the abstract of

We have proposed a set of principles based on the observation that almost all life is sustained by hierarchical branching networks, which we assume have invariant terminal units, are space-filling and are optimised by the process of natural selection. We show how these general constraints explain quarter power scaling and lead to a quantitative, predictive theory that captures many of the essential features of diverse biological systems. Examples considered include animal circulatory systems, plant vascular systems, growth, mitochondrial densities, and the concept of a universal molecular clock. Temperature considerations, dimensionality and the role of invariants are discussed. Criticisms and controversies associated with this approach are also addressed.

A Science article of theirs containing similar ideas:;284/5420/1677

Edit: A recent Nature article showing that there is systematic deviations from the power law, somewhat explainable with a modified version of the model of West and Brown:

To convey an idea that is obvious in retrospect, an idea you can be confident in immediately

Solutions to hard puzzles are good examples of these. NP-problems, where finding a solution is (believed to be) exponentially harder than checking the correctness of it, is the extreme case.

It's called an improper prior. There's been some argument about their use but they seldom lead to problems. The posteriors usually has much better behavior at infinity and when they don't, that's the theory telling us that the information doesn't determine the solution to the problem.

The observation that an improper prior cannot be obtain as a posterior distribution is kind of trivial. It is meant to represent a total lack of information w.r.t. some parameter. As soon you have made an observation you have more information than that.

[Sorry for not answering earlier, I didn't find the inbox until recently.]

I perhaps was a bit unclear, but when I say "ideal bayesian" I mean a mathematical construct that does full bayesian updating i.e. incorporates all prior knowledge into its calculations. This is of course impossible for anyone not extremely ignorant of the world, which is why I called it a minor point.

An ideal bayesian calculation would include massive deductive work on e.g. the psychology of voting, knowledge of the functioning of this community in particular etc.

My comment wasn't really an objection. To do a full bayesian calculation of a real world problem is comparable to using quantum mechanics for macroscopic systems. One must use approximations; the hard part is knowing when they break down.

Reading the Wikipedia article on hyperbolic discounting it seems like there is some evidence for a quasi-hyperbolic discounting. Looking at the formula, the interpretation is exponential discounting for all future times considered but with a special treatment of the present.

How to explain this? It is not unlikely that the brain uses one system for thinking about now and another about the future. Considering the usual workings of evolution, the latter is most likely a much later feature than the former. Considering this, one could perhaps even argue that it would be surprising if there wasn't any differences between the systems.

There seems to be some literature referenced at the wiki article. I suggest looking into it if you are interested. I sadly don't have the time right now.

This is a project that I think really would profit from recruitment of a few psychologists with experience on creating personality test, IQ test or similarly. It sounds a bit like we're trying to create a new subfield here. Not that I want to sound discouraging, I think it is very important to get the ball rolling and even small, preliminary results could prove to be very useful, but there is probably enough material here to base quite a few academic careers on.

I'll have to agree with Kaj that a short survey is better for most purposes, but throwing out a long list of ideas first to later hone down to a more efficient one is a good idea.

I think you may very well be correct in your interpretation of the original authors intention. However, I think Yvain's is more spot on for the majority of the upvotes the comment got.

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