Unrelated to all that, 9/13 edition

I started blogging again after a couple of months hiatus (which I will blame on finishing up a manuscript whose intensity escaped me). Photo from A Beautiful Collection of Insects.

On the blog

This week I posted Eric Kandel’s article on the “new science of mind”, reviewed an article on a method for extracting social interactions that was applied to mice, and wondered about the behavioral effects of computational complexity on Nash equilibria.

Around other blogs

On the practicality of calculating evolutionary equilibria

A discussion of a classic paper that sits at the interface of ecology, evolution and behavior

On the sister blog

The breathing earth

In which Harvard Business School is revealed to be an episode of Gossip Girl

Some gifs of Buster Keaton

Two minutes of Tom Waits pacing

A journey into Rome

I’m a sucker for tilt-shift images

Found in a stray browser tab: The Enigma of Amigara Fault

Haruki Murakami is probably not getting the Nobel Prize this year

Ivan The Terrible goes batshit crazy

A day in the life of a bench, and other illustrations

Movement of the magnetic poles

The History of US population growth

Why was Spinoza excommunicated?

The concept of negative concord

 

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One thought on “Unrelated to all that, 9/13 edition

  1. Thanks for the link!

    A pedantic point: the intended conclusion of the evolutionary equilibria paper is meant to be a little bit deeper than ‘practicality of calculation’. Unless you mean ‘practicality of calculation’ in its broadest sense of ‘achievable by nature’.

    The goal of the algorithmic lens, is not to make computer programs to use as calculation aids by scientists. Computational biology/bioinformatics already does this, and I think it is boring (as I explain in the opening of this post). The goal of the algorithmic lens is to point out that any mechanistic theory is fundamentally an algorithmic objects, and thus a theoretical computer science treatment of it is just an extension of logical analysis (something I talk about more in the context of algorithmic philosophy). As such, when I show that a theory of evolution results in non-tractable computations for finding a local equilibrium, this means that this theory predicts that biological evolution cannot always find local equilibria even in static fitness landscapes. If we are unhappy with this conclusion (or if it is invalidated by experiment) then the corresponding theory has been falsified and we need to revise it. Practically, such a revision would include a formal rule explaining what kind of fitness landscapes are biologically feasible and what kind are not.

    I am going off on a bit of a rant now, sorry! If you want to chat more about this, drop a comment on the evolutionary equilibria post and we can talk there.

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