Supply and demand as driving forces behind biological evolution
February 2, 2019 4 Comments
Recently I was revisiting Xue et al. (2016) and Julian Xue’s thought on supply-driven evolution more generally. I’ve been fascinated by this work since Julian first told me about it. But only now did I realize the economic analogy that Julian is making. So I want to go through this Mutants as Economic Goods metaphor in a bit of detail. A sort of long-delayed follow up to my post on evolution as a risk-averse investor (and another among many links between evolution and economics).
Let us start by viewing the evolving population as a market — focusing on the genetic variation in the population, in particular. From this view, each variant or mutant trait is a good. Natural selection is the demand. It prefers certain goods over others and ‘pays more’ for them in the currency of fitness. Mutation and the genotype-phenotype map that translates individual genetic changes into selected traits is the supply. Both demand and supply matter to the evolutionary economy. But as a field, we’ve put too much emphasis on the demand — survival of the fittest — and not enough emphasis on the supply — arrival of the fittest. This accusation of too much emphasis on demand has usually been raised against the adaptationist program.
The easiest justification for the demand focus of the adapatationist program has been one of model simplicity — similar to the complete market models in economics. If we assume isotropic mutations — i.e. there is the same unbiased chance of a trait to mutate in any direction on the fitness landscape — then surely mutation isn’t an important force in evolution. As long as the right genetic variance is available then nature will be able to select it and we can ignore further properties of the mutation operator. We can make a demand based theory of evolution.
But if only life was so simple.
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Local maxima and the fallacy of jumping to fixed-points
March 29, 2019 by Artem Kaznatcheev 6 Comments
An economist and a computer scientist are walking through the University of Chicago campus discussing the efficient markets hypothesis. The computer scientist spots something on the pavement and exclaims: “look at that $20 on the ground — seems we’ll be getting a free lunch today!”
The economist turns to her without looking down and replies: “Don’t be silly, that’s impossible. If there was a $20 bill there then it would have been picked up already.”
This is the fallacy of jumping to fixed-points.
In this post I want to discuss both the importance and power of local maxima, and the dangers of simply assuming that our system is at a local maximum.
So before we dismiss the economist’s remark with laughter, let’s look at a more convincing discussion of local maxima that falls prey to the same fallacy. I’ll pick on one of my favourite YouTubers, THUNK:
In his video, THUNK discusses a wide range of local maxima and contrasts them with the intended global maximum (or more desired local maxima). He first considers a Roomba vacuum cleaner that is trying to maximize the area that it cleans but gets stuck in the local maximum of his chair’s legs. And then he goes on to discuss similar cases in physics, chemisty, evolution, psychology, and culture.
It is a wonderful set of examples and a nice illustration of the power of fixed-points.
But given that I write so much about algorithmic biology, let’s focus on his discussion of evolution. THUNK describes evolution as follows:
This is a common characterization of evolution. And it seems much less silly than the economist passing up $20. But it is still an example of the fallacy of jumping to fixed-points.
My goal in this post is to convince you that THUNK describing evolution and the economist passing up $20 are actually using the same kind of argument. Sometimes this is a very useful argument, but sometimes it is just a starting point that without further elaboration becomes a fallacy.
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Filed under Commentary Tagged with algorithmic philosophy, classic game theory, economics, evolution, fitness landscapes, philosophy of science, video