Hi Brad,
> > Yes, its amazing what even simple animal brains can do with
> > simple learning problems, when rewards quickly follow
> > behaviors. The forebrain evolved to solve the hard learning
> > problems, when there are long delays between behaviors and
> > rewards, and multiple behaviors prec
>
> Yes, its amazing what even simple animal brains can do with
> simple learning problems, when rewards quickly follow
> behaviors. The forebrain evolved to solve the hard learning
> problems, when there are long delays between behaviors and
> rewards, and multiple behaviors precede rewards. To
On Fri, 21 Feb 2003, Brad Wyble wrote:
> . . .
> Interestingly, there are some primitive parts of our brain that are better at logic
> and are more rational than our executive function. Animals (and humans) in a
> classical conditioning paradigm are *excellent* at performing simple behaviors in
Brad said, responding to Moshe:
> > We have insufficient knowledge, so we need to make some assumptions to
> > approximate P(Xi|Xj). I argue that under these circumstances, the best
> > assumption to make is that Xi and Xj are independent, (ie,
> P(Xi|Xj)=P(Xi)).
> > Does this clarify things?
>
>
>
> Brad wrote:
> > I think this is a core principle of AGI design and that a system that
> > only makes inferences it *knows* are correct would be fairly
> > uninteresting and incapable of performing in the real world. The fact
> > that the information in the P(xi|xj) list is very incomplete is
> This is also an example of how weird the brain can be from an algorithmic
> perspective. In designing an AI system, one tends to abstract cognitive
> processes and create specific processes based on these abstractions. (And
> this is true in NN type AI architectures, not just logicist ones.) B
> Brad wrote:
> > I think this is a core principle of AGI design and that a system that
> > only makes inferences it *knows* are correct would be fairly
> > uninteresting and incapable of performing in the real world. The fact
> > that the information in the P(xi|xj) list is very incomplete is w
Brad wrote:
> I think this is a core principle of AGI design and that a system that
> only makes inferences it *knows* are correct would be fairly
> uninteresting and incapable of performing in the real world. The fact
> that the information in the P(xi|xj) list is very incomplete is what
> makes
> > Hi Ben,
> >
> > Thanks for the brain teaser! As a sometimes believer in
> Occam's Razor, I
> > think it makes sense to assume that Xi and Xj are indepenent,
> unless we know
> > otherwise. This simplifies things, and is the "rational" thing
> to do (for
> > some definition of rational ;->).
> Lakoff and Nunez
> (http://perso.unifr.ch/rafael.nunez/reviews.html) have a theory
> that we compare lengths in our head to do arithmetic, when we're
> not using school-learned rules. Our innate mathematical ability
> is based on visuo-spatial comparisons in their view.
>
> This would basically
>
> Hi Ben,
>
> Thanks for the brain teaser! As a sometimes believer in Occam's Razor, I
> think it makes sense to assume that Xi and Xj are indepenent, unless we know
> otherwise. This simplifies things, and is the "rational" thing to do (for
> some definition of rational ;->). So why not con
Hi Ben,
Thanks for the brain teaser! As a sometimes believer in Occam's Razor, I
think it makes sense to assume that Xi and Xj are indepenent, unless we know
otherwise. This simplifies things, and is the "rational" thing to do (for
some definition of rational ;->). So why not construct a bayes
>
> 1) Humans use special-case algorithms to solve these problem, a different
> algorithm for each domain
>
> 2) Humans have a generalized mental tool for solving these problems, but
> this tool can only be invoked when complemented by some domain-specific
> knowledge
>
> My intuitive inclinat
> > The problem at hand is, you're given some absolute and
> > some conditional probabilities regarding the concepts
> > at hand, and you want to infer a bunch of others.
>
> Hmm. The think I find interesting here is that humans don't have a good
> solution to this problem. Give a typical human a
Ben Goertzel wrote:
> Suppose you have a large set of people, say, all the people on Earth
>
> Then you have a bunch of categories you're interested in, say:
...
> The problem at hand is, you're given some absolute and
> some conditional probabilities regarding the concepts
> at hand, and you wan
> I think I proposed about 6 or so basic variations on this
> theme to test the reasoning system's ability with deal with
> various level or noise and missing data... you can come up
> with all sorts of interesting variations with a bit of thought.
>
> Yeah, just a fancy Venn diagram really used
: "Ben Goertzel" <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Subject: RE: [agi] A probabilistic/algorithmic puzzle...
Date sent: Thu, 20 Feb 2003 14:25:54 -0500
Send reply to: [EMAIL PROTECTED]
OK... lif
Hi Cliff and others,
As I came up with this kind of a test perhaps I should
say a few things about its motivation...
The problem was that the Webmind system had a number of
proposed reasoning systems and it wasn't clear which was
the best. Essentially the reasoning systems took as input
a whole
> Isn't there some way, if a "full curve" is too computationally
> exensive, some way of expressing, say, 2 sigmas (standard deviations)
> or whatever? E.g. 74% will fall within 1 standard dev. of optimum X?
We tried that, but generally, after a few inference iterations, the
confidence intervals
Thursday, February 20, 2003, 8:11:48 PM, Ben Goertzel wrote:
CS> Somehow I see this ending up as finding a set a bell curves (i.e.
CS> their height, spread and optimum) for each estimate. That is to say I
CS> don't see *just* the probability as relevant but the probability
CS> distribution...if I
Hi Cliff,
> BG> One thing that complicates the problem is that ,in some
> cases, as well as
> BG> inferring probabilities one hasn't been given, one may want to make
> BG> corrections to probabilities one HAS been given. For
> instance, sometimes
> BG> one may be given inconsistent information,
---
> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]]On
> Behalf Of Brad Wyble
> Sent: Thursday, February 20, 2003 3:26 PM
> To: [EMAIL PROTECTED]
> Subject: Re: [agi] A probabilistic/algorithmic puzzle...
>
>
> >
> > But anyway, using the weighted-averaging rule dy
Thursday, February 20, 2003, 2:25:54 PM, Ben Goertzel wrote:
BG> The basic situation can be thought of as follows.
Thanks, this does clarify things a lot. Your first statement of the
problem did leave some things out though...but, perhaps
unsurprisingly, I'm still a bit puzzled.
I don't mean
>
> But anyway, using the weighted-averaging rule dynamically and iteratively
> can lead to problems in some cases. Maybe the mechanism you suggest -- a
> nonlinear average of some sort -- would have better behavior, I'll think
> about it.
The part of the idea that guaranteed an eventual equilib
> If P1 and P2 are contradictory, compare the truth values of the
> assertions. If they are very similar, do nothing, because it's
> impossible to know which is correct. If they vary
> significantly(and at least one of them is above a certain
> threshold), alter the probabilities towards one ano
>
> One thing that complicates the problem is that ,in some cases, as well as
> inferring probabilities one hasn't been given, one may want to make
> corrections to probabilities one HAS been given. For instance, sometimes
> one may be given inconsistent information, and one has to choose which
>
EMAIL PROTECTED]Subject: Re: [agi] A probabilistic/algorithmic
puzzle...
Isn't this problem made more complex when we
consider that things belong to various categories.
For instance, if we know that
-40% of americans are fat
-americans are "people"
-a person can b
PM
Subject: RE: [agi] A
probabilistic/algorithmic puzzle...
OK... life lesson
#567: When a mathematical explanation confuses non-math people, another
mathematical explanation is not likely to help
The basic
situation can be thought of as follows.
Suppose you have
OK... life lesson
#567: When a mathematical explanation confuses non-math people, another
mathematical explanation is not likely to help
The basic situation
can be thought of as follows.
Suppose you have a
large set of people, say, all the people on Earth
Then you have a
bunch of ca
> BG> I don't know if this "test problem" will clarify things or
> confuse them ;-)
>
> For me, it's confused them. I thought I was following it before,
> sorta...
OK, well I'm pressed for time today, so I'll write a nonmathematical version
of the problem late tonight or tomorrow or over the wee
Thursday, February 20, 2003, 10:58:57 AM, Ben Goertzel wrote:
BG> OK... I can see that I formulated the problem too formally for a lot of
BG> people
BG> I will now rephrase it in the context of a specific "test problem."
BG> I don't know if this "test problem" will clarify things or confuse t
k parameters of Novamente's
first-order inference module (which embodies one solution to the
problem)...
--
Ben
-Original Message-From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED]]On Behalf Of Jonathan
StandleySent: Thursday, February 20, 2003 4:25 AMTo:
[EMAIL
Thursday, February 20, 2003, 4:25:24 AM, Jonathan Standley wrote:
JS> a challenge! cool :) but let me try to put it in less-math terms
JS> for myself and others who are not math-types
BG>Let X_i, i=1,...,n, denote a set of discrete random variables
JS> X_i is the set of all integers between i
>Let X_i, i=1,...,n, denote a set of discrete
random variables
X_i is the set of all integers
between i and n, initial value for i is 1?
or is i any member of the set
X?
or does i function only as a lower
bound to set X?
hi me again. if forgot to ask: is
i
a challenge! cool :) but let me
try to put it in less-math terms for myself and others who are not
math-types
>Let X_i, i=1,...,n, denote a set of discrete
random variables
X_i is the set of all integers
between i and n, initial value for i is 1?
or is i any member of the set
X?
or do
Hi,
This one is for the more mathematically/algorithmically inclined people on
the list.
I'm going to present a mathematical problem that's come up in the Novamente
development process. We have two different solutions for it, each with
strengths and weaknesses. I'm curious if, perhaps, someone
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