Back in 1987, during my M.Sc., I invented the term 'dynamic relaxation'
to describe a quasi-neural system whose dynamics were governed by
multiple relaxation targets that are changing all the time. So the idea
of having a multi-lobe attractor, or structured, time-varying
attractors, is not by itself a big deal (you can get that sort of
characteristic, I would suspect, in an unlimited number of different
ways, with both simple NNs and with the more exotic types I was
considering), what matters is what you do with it.
What Rabinovich et al appear to do is to buy some mathematical
tractability by applying their idea to a trivially simple neural model.
That means they know a lot of detail about a model that, if used for
anything realistic (like building an intelligence) would *then* beg so
many questions that .... well, it would beg virtually *all* the
questions about what it takes to be intelligent. (I.e. Show me a great
supervised NN and I will show you a very big list of begged questions
about the intelligent functions that have to be in the "supervisor").
In other words, what they have done with it is something essentially
useless. I say that purely because of all those begged questions.
Richard Loosemore.
Ben Goertzel wrote:
About
> http://www.physorg.com/news82190531.html
>
> "Rabinovich and his colleague at the Institute for Nonlinear Science
at the
> University of California, San Diego, Ramon Huerta, along with Valentin
> Afraimovich at the Institute for the Investigation of Optical
Communication
> at the University of San Luis Potosi in Mexico, present a new model for
> understanding decision making. Their paper, titled "Dynamics of
Sequential
> Decision Making," has been published on Physical Review Letters."
I did not read the paper (as it is not available free online) but at
this page
http://inls.ucsd.edu/wlc_locust.html
I found a powerpoint that illustrates the main idea, and points to a
number of related papers with abstracts online.
I think the basic idea they describe is probably sound, although not
as new as they suggest, and not deserving of the hype used to describe
it.
There has long been a question regarding the best way to apply
nonlinear dynamics concepts to the brain. At first, naively, it was
proposed that ideas, memories, perceptions, etc. should be viewed as
**attractors** of neurodynamics -- but eventually folks realized that
the brain rarely settles into attractors in the dynamical systems
theory sense, so that (much as in the dynamical systems theory
analysis of financial time series, for example) one is generally
dealing with complex dynamics of **transients** rather than
attractors.
What Rabinovich et al are saying is, in essence, that neural systems
are characterized by complex attractors with multiple "lobes", and
that decision-making often boils down (at the neurodynamic level) to
the neural net state switching between one lobe or another of the
multi-lobe attractor -- during the "transient" period while the
dynamics is "converging" to the attractor (but note that in a
real-life neurodynamic context, convergence basically never happens
because of new stimuli coming into the brain and perturbing the state
in another direction...).
So, then you can look at a probabilistic model of switching between
lobes of the attractor -- a kind of Markov chain model where the
states are attractor-lobes and (in the simplest case) there is a
matrix of transition probabilities between attractor-lobes. And in
general this will be a Markov process with history.
The notion of attractors with lobes is loosely related to the notion
of hyperchaos
http://www.scholarpedia.org/article/Hyperchaos
which treats attractors with multiple Liapunov exponents.
I wrote about this sort of thing in 1994 in the book Chaotic Logic,
see e.g. section 2.3.2 at the end of
http://www.goertzel.org/books/logic/chapter_two.htm
Rabinovich et al are getting at a similar idea, but in extremely
simple contexts (e.g. behavior of insects and mollusks)....
Is this a "window on consciousness", as Rabinovich describes? Well,
sure it is, in a sense that consciousness is related to making
decisions, and it's interesting to observe how decision-making may
resolve itself in terms of complex nonlinear neurodynamics. But this
kind of observation (about the neurodynamic correlates of
decision-making experience) is of course only a small part of the
picture regarding consciousness, or decision-making, or intelligence,
etc.
-- Ben G
-----
This list is sponsored by AGIRI: http://www.agiri.org/email
To unsubscribe or change your options, please go to:
http://v2.listbox.com/member/?list_id=303
-----
This list is sponsored by AGIRI: http://www.agiri.org/email
To unsubscribe or change your options, please go to:
http://v2.listbox.com/member/?list_id=303
