Tony Bell: Difference between revisions
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The clues to (2) and (3) lie in (1). <br> | The clues to (2) and (3) lie in (1). <br> | ||
I am working on (1) and I think I've got it. | I am working on (1) and I think I've got it. | ||
The reinforcement literature has nothing relevant to say about these deep problems. | |||
And unfortunately there's no way around it: to really crack this we are going to have to "get real". <br> | And unfortunately there's no way around it: to really crack this we are going to have to "get real". <br> | ||
We will have to absorb and augment the emerging non-equilibrium statistical mechanics and (cough) quantum theory. <br> | We will have to absorb and augment the emerging non-equilibrium statistical mechanics and (cough) quantum theory. <br> | ||
I know this is not a common view, but still, I think it is correct. | I know this is not a common view, but still, I think it is correct. Fortunately, both these branches of physics, in their core form, are relatively simple. | ||
Here's an unsatisfactory paper [http://redwood.berkeley.edu/tony/papers Towards a cross-level theory of neural learning] that explains what I was thinking up till about 2008. | Here's an unsatisfactory paper [http://redwood.berkeley.edu/tony/papers Towards a cross-level theory of neural learning] that explains what I was thinking up till about 2008. | ||
Here is my [http://www.kosmix.com/topic/tony_bell CV]. (Ignore the stuff about the cyclist journalist - that's not me :) | Here is my [http://www.kosmix.com/topic/tony_bell CV]. (Ignore the stuff about the cyclist journalist - that's not me :) |
Revision as of 09:08, 9 September 2010
Anthony J. Bell Ph.D.
Redwood Center for Theoretical Neuroscience
UC Berkeley
132 Barker, MC #3190
Berkeley, CA 94720-3190
phone (415) 699 6502
fax (510) 643-4952
tbell@berkeley.edu
Research Interest
It's 2010.
Here's my Salk web-page from way back.
Here's me giving a 30 minute talk Levels, Time and Models about Levels in Biology.
Here's me giving a 85 minute talk Emergence and Submergence in the Nervous System.
(The production on the latter is not so good, so here are the slides.
Also, a few minutes in, the audio drastically improves.)
What am I doing? If you watch either of these you will see, at least, where I am starting from.
I really want to crack this, and I think it can be done before too long.
Also, I believe we must solve these problems.
There are 3 steps to uniting physics, biology and machine learning:
(1) Solve the time series density estimation problem
(2) Solve the sensory-motor problem
(3) Solve the levels problem
The clues to (2) and (3) lie in (1).
I am working on (1) and I think I've got it.
The reinforcement literature has nothing relevant to say about these deep problems.
And unfortunately there's no way around it: to really crack this we are going to have to "get real".
We will have to absorb and augment the emerging non-equilibrium statistical mechanics and (cough) quantum theory.
I know this is not a common view, but still, I think it is correct. Fortunately, both these branches of physics, in their core form, are relatively simple.
Here's an unsatisfactory paper Towards a cross-level theory of neural learning that explains what I was thinking up till about 2008.
Here is my CV. (Ignore the stuff about the cyclist journalist - that's not me :)