

Predictive brains, situated agents and future of cognitive science (2013) [pdf] - gwern
https://dl.dropboxusercontent.com/u/280585369/2013-clark.pdf

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hyperion2010
I find this an amusingly cognitive view. I think the commentators do a pretty
good job of dealing with the main issues. Yes, you could frame everything as
'prediction' but basically all you are doing is conflating 'prediction' with
'agency with a time delay.' This really doesn't solve any problems. At what
timescale you want to draw the line between prediction and agency for closed
loop systems is an open question. I think one of the key concepts that the
author fails to address is that the fundamental problem the nervous system
addresses is coordination of otherwise isolated muscles, organs etc. While we
may remain mystified about the function of the mind, we do know that at some
level the nervous system is really about control and synchronization. There
are astoundingly good models (now with biological correlates!) of motor
control loops that are just classic PID controllers. While the predictive
perspective can be useful in some cases it is just a perspective and an
interpretation. If you want to get to the heart of the matter you need math,
and this paper is lacking on the math. To paraphrase: words are wind, math is
truth.

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Cheatboy2
Your comment lacks of math though.

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Houshalter
Exactly. Why intentionally obscure stuff with math if you don't have to? What
a silly bias.

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dil8
Doesn't it work the other way... Math provides clarity where as words can be
ambiguous.

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Houshalter
I've never had that experience. It usually takes a lot more effort effort to
work out what the math is actually describing and why the operations done on
it make sense. That's if I even understand the symbols and functions they use.
If not then it's totally inaccessible.

To be fair you can easily obscure natural language in similar ways.

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sdgsdgsdg
Perhaps the brain just provides a place for the patterns to live? Perhaps it
is not so much searching for patterns of activity which allow it to predict
the future, but allowing the patterns of activity induced by the world to grow
and evolve together. Then all it has to do is modulate this evolution when the
organism gets something it likes. Reward modulated hebbian learning I believe
it is called. I've not read the whole paper, but it seems overly complicated
and unnecessary when you consider the above conception...

