Re: [FRIAM] Fwd: In Memoriam: Thomas C. Schelling

[Steven A Smith]

All the old men (and women) are dying!

Is it a sign or is it a portent of things to come that Leonard Cohen and 
Fidel Castro both checked out soon with the election!?


Thanks Roger for letting us know about Weininger and Fienberg... I 
hadn't heard.



On 12/14/16 7:45 PM, Roger Critchlow wrote:
Ah,the mortality is getting thick.  My high school buddy Aaron had a 
fatal massive heart attack in August.  My sister-in-law Mimi succumbed 
to cancer on October 30 while I was flying back from visiting her and 
my brother.  Dave Weininger, master of chemical information, passed 
away on November 2.  Cosma Shalizi has posted a memoriam for Stephen 
E. Fienberg today on his weblog, his first entry since the end of 
August.  You begin to worry about the people you haven't checked in 
with lately.


-- rec --

On Wed, Dec 14, 2016 at 8:38 PM, Merle Lefkoff > wrote:


Thanks so much for the memory--one of my first aha! moments as I
discovered Complexity science was watching Schelling's segregation
ABM.

On Wed, Dec 14, 2016 at 5:29 PM, Stephen Guerin
>
wrote:

A message from Yaneer:


In Memoriam: Thomas C. Schelling
December 13, 2016

Tom Schelling, master of the important idea in a complex
world, passed away, Tuesday, December 13, 2016. His work on
mutual assured destruction and on segregation showed he knew
what the most important questions were and had the ability to
answer them. In each case we gained new insight as well as
essential aspects of dealing with important real world problems.

In the former, he identified the way we could survive nuclear
confrontation between the US and Soviet Union, showing the way
to stability through mutual assured destruction---whose
recognition would provide not just deterrence but calming
assurance---an incredible force for peaceful coexistence in a
century of the massive conflicts in world wars and political
uncertainty that actions might be taken leading to global
destruction.

In the latter, he recognized the central insight of complex
systems science, the ability of individual agent choices to
result in collective behavior s. He understood that the
connection between them might, and often is, not clear to a
casual observer, but yields to the right kind of analysis. In
this case, the choice of individuals who prefer to live near
others of the same type, manifests in the creation of
segregated communities.

Both of these contributions to our understanding reflect deep
and important questions, and remarkably clear and (in
retrospect) simple answers. And the answers were, and are,
essential to our understanding of the world around us and the
challenges we are facing.

This spring when I learned of concerns about North Korea from
the National Security Council and the Defense Threat Reduction
Agency, I spoke with Tom to learn from his insights into this
version of the nuclear confrontation. He was clear and
straightforward in his view that we should not be concerned,
and should not act with concern. After some thought about the
unique conditions of the North Korea confrontation, I unde
rstood better not only the reason for his statements but their
wisdom---one of the greatest destabilizing forces is the
concern itself.

Perhaps we should formally define the difference between
intelligent and wise as the ability to include one's own words
into the frame of analysis.

I am sure I still have much to learn from Tom and will be
reading his papers and books for years to come. Still, I will
miss the chance to talk with him.

There are many who have gained from his intellectual
contributions, there are few if any who have not benefitted
from his wisdom. We are diminished at his passing.

Yaneer Bar-Yam, New England Complex Systems Institute,
Cambridge, MA

New England Complex Systems Institute

New England Complex Systems Institute
210 Broadway Suite 101
Cambridge, MA 02139
Phone: 617-547-4100 
Fax: 617-661-7711 
necsi.edu 

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FRIAM Applied 

Re: [FRIAM] Fwd: In Memoriam: Thomas C. Schelling

[Frank Wimberly]

Yes, having left Carnegie Mellon in 1998 I occasionally inquire about
former colleagues only to learn that they are deceased. Fienberg's office
was down the hall from mine but I didn't know him well.  On the other hand
I can count about 10 whom I did know well.  Most were younger than I.

Did you answer Nick about the bubble's performance in very cold weather.

Frank

Frank

Frank Wimberly
Phone (505) 670-9918

On Dec 14, 2016 7:45 PM, "Roger Critchlow"  wrote:

Ah, the mortality is getting thick.  My high school buddy Aaron had a fatal
massive heart attack in August.  My sister-in-law Mimi succumbed to cancer
on October 30 while I was flying back from visiting her and my brother.
Dave Weininger, master of chemical information, passed away on November 2.
Cosma Shalizi has posted a memoriam for Stephen E. Fienberg today on his
weblog, his first entry since the end of August.  You begin to worry about
the people you haven't checked in with lately.

-- rec --

On Wed, Dec 14, 2016 at 8:38 PM, Merle Lefkoff 
wrote:

> Thanks so much for the memory--one of my first aha! moments as I
> discovered Complexity science was watching Schelling's segregation ABM.
>
> On Wed, Dec 14, 2016 at 5:29 PM, Stephen Guerin <
> stephen.gue...@simtable.com> wrote:
>
>> A message from Yaneer:
>>
>>
>> In Memoriam: Thomas C. Schelling
>> December 13, 2016
>>
>> Tom Schelling, master of the important idea in a complex world, passed
>> away, Tuesday, December 13, 2016. His work on mutual assured destruction
>> and on segregation showed he knew what the most important questions were
>> and had the ability to answer them. In each case we gained new insight as
>> well as essential aspects of dealing with important real world problems.
>>
>> In the former, he identified the way we could survive nuclear
>> confrontation between the US and Soviet Union, showing the way to stability
>> through mutual assured destruction---whose recognition would provide not
>> just deterrence but calming assurance---an incredible force for peaceful
>> coexistence in a century of the massive conflicts in world wars and
>> political uncertainty that actions might be taken leading to global
>> destruction.
>>
>> In the latter, he recognized the central insight of complex systems
>> science, the ability of individual agent choices to result in collective
>> behavior s. He understood that the connection between them might, and often
>> is, not clear to a casual observer, but yields to the right kind of
>> analysis. In this case, the choice of individuals who prefer to live near
>> others of the same type, manifests in the creation of segregated
>> communities.
>>
>> Both of these contributions to our understanding reflect deep and
>> important questions, and remarkably clear and (in retrospect) simple
>> answers. And the answers were, and are, essential to our understanding of
>> the world around us and the challenges we are facing.
>>
>> This spring when I learned of concerns about North Korea from the
>> National Security Council and the Defense Threat Reduction Agency, I spoke
>> with Tom to learn from his insights into this version of the nuclear
>> confrontation. He was clear and straightforward in his view that we should
>> not be concerned, and should not act with concern. After some thought about
>> the unique conditions of the North Korea confrontation, I unde rstood
>> better not only the reason for his statements but their wisdom---one of the
>> greatest destabilizing forces is the concern itself.
>>
>> Perhaps we should formally define the difference between intelligent and
>> wise as the ability to include one's own words into the frame of analysis.
>>
>> I am sure I still have much to learn from Tom and will be reading his
>> papers and books for years to come. Still, I will miss the chance to talk
>> with him.
>>
>> There are many who have gained from his intellectual contributions, there
>> are few if any who have not benefitted from his wisdom. We are diminished
>> at his passing.
>>
>> Yaneer Bar-Yam, New England Complex Systems Institute, Cambridge, MA
>>
>> [image: New England Complex Systems Institute]
>>
>> New England Complex Systems Institute
>> 210 Broadway Suite 101
>> Cambridge, MA 02139
>> Phone: 617-547-4100 <(617)%20547-4100>
>> Fax: 617-661-7711 <(617)%20661-7711>
>> necsi.edu
>>
>> ---
>>
>> To unsubscribe from the cx-web list, please FORWARD this message to 
>> progr...@necsi.edu, EDIT the subject to read "Unsubscribe" and include all 
>> alternate email addresses in the body of your message. Do not reply to this 
>> message.
>>
>>
>>
>> 
>> FRIAM Applied Complexity Group listserv
>> Meets Fridays 9a-11:30 at cafe at St. John's College
>> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
>> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>>
>
>
>
> --
> Merle Lefkoff, Ph.D.
> President, 

Re: [FRIAM] Fwd: In Memoriam: Thomas C. Schelling

[Merle Lefkoff]

You're right, Roger.  We must pay more attention to the dearest live ones.

On Wed, Dec 14, 2016 at 7:45 PM, Roger Critchlow  wrote:

> Ah, the mortality is getting thick.  My high school buddy Aaron had a
> fatal massive heart attack in August.  My sister-in-law Mimi succumbed to
> cancer on October 30 while I was flying back from visiting her and my
> brother.  Dave Weininger, master of chemical information, passed away on
> November 2.  Cosma Shalizi has posted a memoriam for Stephen E. Fienberg
> today on his weblog, his first entry since the end of August.  You begin to
> worry about the people you haven't checked in with lately.
>
> -- rec --
>
> On Wed, Dec 14, 2016 at 8:38 PM, Merle Lefkoff 
> wrote:
>
>> Thanks so much for the memory--one of my first aha! moments as I
>> discovered Complexity science was watching Schelling's segregation ABM.
>>
>> On Wed, Dec 14, 2016 at 5:29 PM, Stephen Guerin <
>> stephen.gue...@simtable.com> wrote:
>>
>>> A message from Yaneer:
>>>
>>>
>>> In Memoriam: Thomas C. Schelling
>>> December 13, 2016
>>>
>>> Tom Schelling, master of the important idea in a complex world, passed
>>> away, Tuesday, December 13, 2016. His work on mutual assured destruction
>>> and on segregation showed he knew what the most important questions were
>>> and had the ability to answer them. In each case we gained new insight as
>>> well as essential aspects of dealing with important real world problems.
>>>
>>> In the former, he identified the way we could survive nuclear
>>> confrontation between the US and Soviet Union, showing the way to stability
>>> through mutual assured destruction---whose recognition would provide not
>>> just deterrence but calming assurance---an incredible force for peaceful
>>> coexistence in a century of the massive conflicts in world wars and
>>> political uncertainty that actions might be taken leading to global
>>> destruction.
>>>
>>> In the latter, he recognized the central insight of complex systems
>>> science, the ability of individual agent choices to result in collective
>>> behavior s. He understood that the connection between them might, and often
>>> is, not clear to a casual observer, but yields to the right kind of
>>> analysis. In this case, the choice of individuals who prefer to live near
>>> others of the same type, manifests in the creation of segregated
>>> communities.
>>>
>>> Both of these contributions to our understanding reflect deep and
>>> important questions, and remarkably clear and (in retrospect) simple
>>> answers. And the answers were, and are, essential to our understanding of
>>> the world around us and the challenges we are facing.
>>>
>>> This spring when I learned of concerns about North Korea from the
>>> National Security Council and the Defense Threat Reduction Agency, I spoke
>>> with Tom to learn from his insights into this version of the nuclear
>>> confrontation. He was clear and straightforward in his view that we should
>>> not be concerned, and should not act with concern. After some thought about
>>> the unique conditions of the North Korea confrontation, I unde rstood
>>> better not only the reason for his statements but their wisdom---one of the
>>> greatest destabilizing forces is the concern itself.
>>>
>>> Perhaps we should formally define the difference between intelligent and
>>> wise as the ability to include one's own words into the frame of analysis.
>>>
>>> I am sure I still have much to learn from Tom and will be reading his
>>> papers and books for years to come. Still, I will miss the chance to talk
>>> with him.
>>>
>>> There are many who have gained from his intellectual contributions,
>>> there are few if any who have not benefitted from his wisdom. We are
>>> diminished at his passing.
>>>
>>> Yaneer Bar-Yam, New England Complex Systems Institute, Cambridge, MA
>>>
>>> [image: New England Complex Systems Institute]
>>>
>>> New England Complex Systems Institute
>>> 210 Broadway Suite 101
>>> Cambridge, MA 02139
>>> Phone: 617-547-4100 <(617)%20547-4100>
>>> Fax: 617-661-7711 <(617)%20661-7711>
>>> necsi.edu
>>>
>>> ---
>>>
>>> To unsubscribe from the cx-web list, please FORWARD this message to 
>>> progr...@necsi.edu, EDIT the subject to read "Unsubscribe" and include all 
>>> alternate email addresses in the body of your message. Do not reply to this 
>>> message.
>>>
>>>
>>>
>>> 
>>> FRIAM Applied Complexity Group listserv
>>> Meets Fridays 9a-11:30 at cafe at St. John's College
>>> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
>>> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>>>
>>
>>
>>
>> --
>> Merle Lefkoff, Ph.D.
>> President, Center for Emergent Diplomacy
>> Santa Fe, New Mexico, USA
>> merlelef...@gmail.com
>> mobile:  (303) 859-5609
>> skype:  merle.lelfkoff2
>>
>> 
>> FRIAM 

Re: [FRIAM] Fwd: In Memoriam: Thomas C. Schelling

[Roger Critchlow]

Ah, the mortality is getting thick.  My high school buddy Aaron had a fatal
massive heart attack in August.  My sister-in-law Mimi succumbed to cancer
on October 30 while I was flying back from visiting her and my brother.
Dave Weininger, master of chemical information, passed away on November 2.
Cosma Shalizi has posted a memoriam for Stephen E. Fienberg today on his
weblog, his first entry since the end of August.  You begin to worry about
the people you haven't checked in with lately.

-- rec --

On Wed, Dec 14, 2016 at 8:38 PM, Merle Lefkoff 
wrote:

> Thanks so much for the memory--one of my first aha! moments as I
> discovered Complexity science was watching Schelling's segregation ABM.
>
> On Wed, Dec 14, 2016 at 5:29 PM, Stephen Guerin <
> stephen.gue...@simtable.com> wrote:
>
>> A message from Yaneer:
>>
>>
>> In Memoriam: Thomas C. Schelling
>> December 13, 2016
>>
>> Tom Schelling, master of the important idea in a complex world, passed
>> away, Tuesday, December 13, 2016. His work on mutual assured destruction
>> and on segregation showed he knew what the most important questions were
>> and had the ability to answer them. In each case we gained new insight as
>> well as essential aspects of dealing with important real world problems.
>>
>> In the former, he identified the way we could survive nuclear
>> confrontation between the US and Soviet Union, showing the way to stability
>> through mutual assured destruction---whose recognition would provide not
>> just deterrence but calming assurance---an incredible force for peaceful
>> coexistence in a century of the massive conflicts in world wars and
>> political uncertainty that actions might be taken leading to global
>> destruction.
>>
>> In the latter, he recognized the central insight of complex systems
>> science, the ability of individual agent choices to result in collective
>> behavior s. He understood that the connection between them might, and often
>> is, not clear to a casual observer, but yields to the right kind of
>> analysis. In this case, the choice of individuals who prefer to live near
>> others of the same type, manifests in the creation of segregated
>> communities.
>>
>> Both of these contributions to our understanding reflect deep and
>> important questions, and remarkably clear and (in retrospect) simple
>> answers. And the answers were, and are, essential to our understanding of
>> the world around us and the challenges we are facing.
>>
>> This spring when I learned of concerns about North Korea from the
>> National Security Council and the Defense Threat Reduction Agency, I spoke
>> with Tom to learn from his insights into this version of the nuclear
>> confrontation. He was clear and straightforward in his view that we should
>> not be concerned, and should not act with concern. After some thought about
>> the unique conditions of the North Korea confrontation, I unde rstood
>> better not only the reason for his statements but their wisdom---one of the
>> greatest destabilizing forces is the concern itself.
>>
>> Perhaps we should formally define the difference between intelligent and
>> wise as the ability to include one's own words into the frame of analysis.
>>
>> I am sure I still have much to learn from Tom and will be reading his
>> papers and books for years to come. Still, I will miss the chance to talk
>> with him.
>>
>> There are many who have gained from his intellectual contributions, there
>> are few if any who have not benefitted from his wisdom. We are diminished
>> at his passing.
>>
>> Yaneer Bar-Yam, New England Complex Systems Institute, Cambridge, MA
>>
>> [image: New England Complex Systems Institute]
>>
>> New England Complex Systems Institute
>> 210 Broadway Suite 101
>> Cambridge, MA 02139
>> Phone: 617-547-4100 <(617)%20547-4100>
>> Fax: 617-661-7711 <(617)%20661-7711>
>> necsi.edu
>>
>> ---
>>
>> To unsubscribe from the cx-web list, please FORWARD this message to 
>> progr...@necsi.edu, EDIT the subject to read "Unsubscribe" and include all 
>> alternate email addresses in the body of your message. Do not reply to this 
>> message.
>>
>>
>>
>> 
>> FRIAM Applied Complexity Group listserv
>> Meets Fridays 9a-11:30 at cafe at St. John's College
>> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
>> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>>
>
>
>
> --
> Merle Lefkoff, Ph.D.
> President, Center for Emergent Diplomacy
> Santa Fe, New Mexico, USA
> merlelef...@gmail.com
> mobile:  (303) 859-5609
> skype:  merle.lelfkoff2
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>

Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[Robert Wall]

Hey Glen,

Yes, on the first issue with respect to the Axiom of Choice, I think the
word "choice" there does not map one-for-one to the same word used in
probability theory. I think the two concepts are mutually exclusive, but
this may be beyond my "pay grade" to worry or talk about. 蘿

However, I can most certainly see your point about the beneficial
relationship between measurement theory and probability theory. The notion
sigma algebra is spot on, especially for the mathematics of theoretical
probability. Even though I may be considered an old dog professionally, I
can still resonate with Grant's notion of probability spaces as well.  It's
all good!

You know, I can still have fun while simultaneously being lost in the
forest. This has been fun!  Thanks for letting me play in the sandbox ... 

Cheers

On Wed, Dec 14, 2016 at 6:50 PM, glen ☣  wrote:

>
> Well, sure.  But the point is that the axiom of choice asserts, merely,
> the existence of the ability to choose a subset.  They call them "choice
> functions", as if there exists some "chooser".  But there's no sense of
> time (before the choice function is applied versus after it's applied).
> The name "choice" is a misleading misnomer.
>
> And that's my point.  Probability theory is a special case of measure
> theory.  Calling the set measures "probabilities" is an antiquated,
> misleading, and unfortunate name.
>
> On 12/14/2016 01:41 PM, Frank Wimberly wrote:
> > Don't think about choosing.  The axiom of choice says that there is a
> function from each set (subset) to an element of itself, as I recall.
>
> --
> ☣ glen
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>

FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[glen ☣]

Well, my question hasn't been addressed satisfactorily.  But I sincerely 
appreciate all the different ways everyone has tried to talk about it.  My 
question is about language, not math or statistics.  I'm adept enough at those. 
 What I'm having trouble with in the argument (the guy's name is Steve, btw) is 
my inability to communicate the measure theory conception of probability theory 
in plain English.  (He's not a mathematician, either.)

I'm especially appreciative of what you, Eric, and Grant have laid out from the 
practical "just get 'er done" perspective.  The reason my initial (failed) joke 
about not understanding what statistics _is_, but claiming to understand what 
probability theory _is_, was a joke, is because both are so heavily applied and 
so lightly ontological.  Were I able to tell the joke so that Steve saw the 
Platonic vs. constructivist, noun vs. verb, (false) dichotomy implied, then I 
wouldn't find myself having to explain it.  I would have avoided the need to 
make the Platonic view explicit ... which would have been good because I'm not 
a Platonist.

On 12/14/2016 05:05 PM, Robert Wall wrote:
> Somehow, I still feel I am missing something. Maybe you can figure it out, 
> but it may not be all that important, and your question may have already been 
> addressed satisfactorily by the other responses posted to the thread. 


-- 
☣ glen


FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[glen ☣]

Well, sure.  But the point is that the axiom of choice asserts, merely, the 
existence of the ability to choose a subset.  They call them "choice 
functions", as if there exists some "chooser".  But there's no sense of time 
(before the choice function is applied versus after it's applied).  The name 
"choice" is a misleading misnomer.

And that's my point.  Probability theory is a special case of measure theory.  
Calling the set measures "probabilities" is an antiquated, misleading, and 
unfortunate name.

On 12/14/2016 01:41 PM, Frank Wimberly wrote:
> Don't think about choosing.  The axiom of choice says that there is a 
> function from each set (subset) to an element of itself, as I recall.

-- 
☣ glen


FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] Fwd: In Memoriam: Thomas C. Schelling

[Merle Lefkoff]

Thanks so much for the memory--one of my first aha! moments as I discovered
Complexity science was watching Schelling's segregation ABM.

On Wed, Dec 14, 2016 at 5:29 PM, Stephen Guerin  wrote:

> A message from Yaneer:
>
>
> In Memoriam: Thomas C. Schelling
> December 13, 2016
>
> Tom Schelling, master of the important idea in a complex world, passed
> away, Tuesday, December 13, 2016. His work on mutual assured destruction
> and on segregation showed he knew what the most important questions were
> and had the ability to answer them. In each case we gained new insight as
> well as essential aspects of dealing with important real world problems.
>
> In the former, he identified the way we could survive nuclear
> confrontation between the US and Soviet Union, showing the way to stability
> through mutual assured destruction---whose recognition would provide not
> just deterrence but calming assurance---an incredible force for peaceful
> coexistence in a century of the massive conflicts in world wars and
> political uncertainty that actions might be taken leading to global
> destruction.
>
> In the latter, he recognized the central insight of complex systems
> science, the ability of individual agent choices to result in collective
> behavior s. He understood that the connection between them might, and often
> is, not clear to a casual observer, but yields to the right kind of
> analysis. In this case, the choice of individuals who prefer to live near
> others of the same type, manifests in the creation of segregated
> communities.
>
> Both of these contributions to our understanding reflect deep and
> important questions, and remarkably clear and (in retrospect) simple
> answers. And the answers were, and are, essential to our understanding of
> the world around us and the challenges we are facing.
>
> This spring when I learned of concerns about North Korea from the National
> Security Council and the Defense Threat Reduction Agency, I spoke with Tom
> to learn from his insights into this version of the nuclear confrontation.
> He was clear and straightforward in his view that we should not be
> concerned, and should not act with concern. After some thought about the
> unique conditions of the North Korea confrontation, I unde rstood better
> not only the reason for his statements but their wisdom---one of the
> greatest destabilizing forces is the concern itself.
>
> Perhaps we should formally define the difference between intelligent and
> wise as the ability to include one's own words into the frame of analysis.
>
> I am sure I still have much to learn from Tom and will be reading his
> papers and books for years to come. Still, I will miss the chance to talk
> with him.
>
> There are many who have gained from his intellectual contributions, there
> are few if any who have not benefitted from his wisdom. We are diminished
> at his passing.
>
> Yaneer Bar-Yam, New England Complex Systems Institute, Cambridge, MA
>
> [image: New England Complex Systems Institute]
>
> New England Complex Systems Institute
> 210 Broadway Suite 101
> Cambridge, MA 02139
> Phone: 617-547-4100 <(617)%20547-4100>
> Fax: 617-661-7711 <(617)%20661-7711>
> necsi.edu
>
> ---
>
> To unsubscribe from the cx-web list, please FORWARD this message to 
> progr...@necsi.edu, EDIT the subject to read "Unsubscribe" and include all 
> alternate email addresses in the body of your message. Do not reply to this 
> message.
>
>
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>



-- 
Merle Lefkoff, Ph.D.
President, Center for Emergent Diplomacy
Santa Fe, New Mexico, USA
merlelef...@gmail.com
mobile:  (303) 859-5609
skype:  merle.lelfkoff2

FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[Robert Wall]

Glen,

Okay, given some of the later postings against the original question, I am
thinking that your question may have morphed or that I have completely
misunderstood what you are asking. Not sure. For example, somehow we have
gone from probability theory and its ontological status to the
Banach-Tarski Theorem and the Axiom of Choice.  This seems like a
non-sequitur, but not sure.  First off, a theory is inductive, whereas, a
theorem is deductive; so that is my first disconnect. So I don't understand
how we got here ... but this often happens to me.  :-(

Then we go to what I think is a refinement of the original question. Yes?
 (I am just trying to navigate the thinking to get to the core issue, that
I seem to be missing):

But what is this "set of events"? That's the question that is being
> discussed on this thread. It turns out that the events for a finite space
> is nothing more than the set of all possible combinations of the sample
> points. (Formally the event set is something called a "sigma algebra", but
> no matter.) So, an event scan be thought of simply all combinations of the
> sample points.


and then to:

So, the events already have probabilities by virtue of just being in a
> probability space. They don't have to be "selected", "chosen" or any such
> thing. They "just sit there" and have probabilities - all of them. The
> notion of time is never mentioned or required.


An event is not *all* the combinations of the sample points.  As Grant has
said, an event [outcome] has probability depending on how it is arbitrarily
configured from the event space by the researcher.  Moreover, there is an
important distinction to be made between the distribution of values [e.g.,
the numbers on each side of a dice being equally likely] and the sampling
distribution that is dependent on how the event is composed in a trial
sequence.  The sampling distribution is the mathematical result of the
convolution of probabilities when choosing N independent, *usually
*identically-distributed
random picks from the parent distribution.

Another example might be helpful: I think you are trying to define the
sample space like with an urn of 10 balls with three red and seven white.
An event, in that case, would be something like picking three balls all
red.  We could easily compute the probability of this event by using
hypergeometric arithmetic; this is because of the sample space changing if
you do not replace any balls after each pick. But, there is a finite number
of other possible events in this scenario of picking three things from a
bin of ten things. To be sure, though, this statistical problem does not
relate at all to the paradoxical Axiom of Choice ... unless I am still
missing something.  We are not interested in slicing and dicing [no pun
intended] a probability space of a certain size in a way for coming up
with, say, two identical but mutually exclusive probability spaces of the
same size. This would make no sense, IMHO.

Events are just the outcome(s) one is interested in computing the
probability for.  They don't exist--as selections, in the way that I think
you mean--until they are formulated by the researcher ... not trying to
conjure up anything spooky here between the observer and the experiment as at
the quantum level. :-) Nor are these events--not being mathematical
entities of any type--something to be discovered in some platonic math
sense [I mistakenly called you a Platonist, but on rereading the thread, I
think you are not. Sorry. But the world wouldn't be as interesting without
Platonists. :-) ].

For example, there is the possible event of being dealt four aces in one
hand of five cards and for which I can assign a probability given the
conceptual structure of the probability space: a deck of cards. This is
nothing more than laying out the number of possible [combinations--so order
doesn't matter] of hands (a sample) and determining how many ways I could
be dealt four aces [just one] ... then dividing the latter by the former.
This is an example of a categorical probability space, where the events are
all the various ways [combinations] one can be dealt five cards from a deck
of 52. We could go on to define these into categories like two of a kind,
three of a kind, and so forth. Each of those events can be then assigned a
probability.

and then:

Perhaps it's helpful to think about the "axiom of choice"?  Is a
> "choosable" element somehow distinct from a "chosen" element?  Does the act
> of choosing change the element in some way I'm unaware of?  Does
> choosability require an agent exist and (eventually) _do_ the choosing?


The Axiom of Choice is a paradox that seems to get into trouble with
set-cardinality, where it comes to infinite sets.  To me is nothing more
than a mathematical curiosity that has no impact on the practical world. So
I don't think this is helpful to your cause. But I would be more than
curious to see how you think it might be. I am more an applied

[FRIAM] Fwd: In Memoriam: Thomas C. Schelling

[Stephen Guerin]

A message from Yaneer:


In Memoriam: Thomas C. Schelling
December 13, 2016

Tom Schelling, master of the important idea in a complex world, passed
away, Tuesday, December 13, 2016. His work on mutual assured destruction
and on segregation showed he knew what the most important questions were
and had the ability to answer them. In each case we gained new insight as
well as essential aspects of dealing with important real world problems.

In the former, he identified the way we could survive nuclear confrontation
between the US and Soviet Union, showing the way to stability through
mutual assured destruction---whose recognition would provide not just
deterrence but calming assurance---an incredible force for peaceful
coexistence in a century of the massive conflicts in world wars and
political uncertainty that actions might be taken leading to global
destruction.

In the latter, he recognized the central insight of complex systems
science, the ability of individual agent choices to result in collective
behavior s. He understood that the connection between them might, and often
is, not clear to a casual observer, but yields to the right kind of
analysis. In this case, the choice of individuals who prefer to live near
others of the same type, manifests in the creation of segregated
communities.

Both of these contributions to our understanding reflect deep and important
questions, and remarkably clear and (in retrospect) simple answers. And the
answers were, and are, essential to our understanding of the world around
us and the challenges we are facing.

This spring when I learned of concerns about North Korea from the National
Security Council and the Defense Threat Reduction Agency, I spoke with Tom
to learn from his insights into this version of the nuclear confrontation.
He was clear and straightforward in his view that we should not be
concerned, and should not act with concern. After some thought about the
unique conditions of the North Korea confrontation, I unde rstood better
not only the reason for his statements but their wisdom---one of the
greatest destabilizing forces is the concern itself.

Perhaps we should formally define the difference between intelligent and
wise as the ability to include one's own words into the frame of analysis.

I am sure I still have much to learn from Tom and will be reading his
papers and books for years to come. Still, I will miss the chance to talk
with him.

There are many who have gained from his intellectual contributions, there
are few if any who have not benefitted from his wisdom. We are diminished
at his passing.

Yaneer Bar-Yam, New England Complex Systems Institute, Cambridge, MA

[image: New England Complex Systems Institute]

New England Complex Systems Institute
210 Broadway Suite 101
Cambridge, MA 02139
Phone: 617-547-4100 <(617)%20547-4100>
Fax: 617-661-7711 <(617)%20661-7711>
necsi.edu

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Re: [FRIAM] Model of induction

[Russell Standish]

On Tue, Dec 13, 2016 at 08:41:12PM -0700, Nick Thompson wrote:
> Hi, Russell S., 
> 
> It's a long time since the old days of the Three Russell's, isn't it?  Where 
> have all the Russell's gone?  Good to hear from you. 
> 
> This has been a humbling experience.  My brother was a mathematician and he 
> used to frown every time asked him what I thought was a simple mathematical 
> question.  
> 
> So ... with my heart in my hands ... please tell me, why a string of 100 
> one's , followed by a string of 100 2's, ..., followed by a string of 100 
> zero's wouldn’t be regarded as random.  There must be something more than 
> uniform distribution, eh?
> 

Yes - the modern notion of a random string is that it is
uncompressible by a Turing machine shorter than itself.

Obviously, you can exploit nonuniformity to provide a compression - eg
the way that 'e' and 't' are represented by single . and -
respectively provides a compression of random English language
phrases. Hence why uniformity is one test of randomness

That is why non-uniform random, whilst a thing, must be defined by an
algorithmic transformation to a uniform random thing (the
algorithmically uncompressible things mentioned above).

> Is there a halting problem lurking here?  
> 

Absolutely.

-- 


Dr Russell StandishPhone 0425 253119 (mobile)
Principal, High Performance Coders
Visiting Senior Research Fellowhpco...@hpcoders.com.au
Economics, Kingston University http://www.hpcoders.com.au



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Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[Robert Wall]

Hi Glen, et al,

Thanks for cashing mu $0.02 check. :-)

When I wrote that "but it doesn't have to be" I wasn't asserting that
probability theory is devoid of events.  Events are fundamental to
probability theory.  They are the outcomes to which probability is
assigned.  In a nutshell, the practice of probability theory is the mapping
of the events--outcomes-- from random processes to numbers, thus making the
practice purposefully mathematical.  And in this regard, we speak of a
mathematical entity dubbed a random variable in order to carry out the
calculus of probability and statistics.

A random variable is like any other variable in mathematics, but with
specific properties concerning the values it can take on.  A random
variable is considered "discrete" if it can take on only countable,
distinct, or separate values [e.g., the sum of the values of a roll of
seven die].  Otherwise, a random variable can be considered "continuous" if
it can take on any value in an interval [e.g., the mass of an animal].
But, a random variable is a real-valued function--a one-to-one mapping of a
random process to a number line.

This is arguably as long about way of explaining [muck?!] why I said "but
it doesn't have to be ... time." Time doesn't have to be involved such that
the random variable does not have to distributed in time but often can be,
such as in reliability theory--for, example, the probability that a device
will survive for at least T cycles or months.

Yes to your and Grant's notion that thinking in terms of probability spaces
is a good way of thinking of probability and statistic and this mapping, as
mathematically we are doing convolutions of distributions [spaces?] when
modeling independent, usually identically distributed random trials
[activities]. But, let's not confuse the mathematical modeling with the
selection process of, say picking four of a kind from a deck of 52 cards.
All we are interested in doing is mapping the outcomes--events-- to
possibilities over which the probabilities all sum or integrate to no more
than unity. The activity gets mapped in the treatment of the random
variable in the mapping [e..g., the number of trials]. So, for example,
rolling 6s six times in a row is not a function of time, but of six
discrete, independent and identically distributed trials. For the computed
probability, in this case, it doesn't matter how long it took to roll the
dice six times.

I am thinking that this is the way your "opponent" is thinking about the
problem and suspect that he has been formally trained to see it this way.
Not the only way but a classical way.

When Eric talks about the historic difference between scientists,
mathematicians, and statisticians practicing probability theory and
statistics, these differences quickly disappeared when the idea of *uncertainty
*bubbled up into the models found in the fields of physics, economics,
measurement theory, decision theory, etc.  No longer could the world be
completely described by the classical system dynamic models.  Maybe before
Gauss even (the late-1700s), who was a polymath to be sure, error terms
were starting to be added to their equations and had to be estimated.

As to my language of "when" an event occurs with some calculated
likelihood, it can be a description or a prediction. The researcher may be
asking like Nick is [kind of?] asking in the other thread, what is the
likelihood of my getting this many 1s in a row if the process is supposedly
generating discrete random numbers between, say, one and five? In this
case, a *psychologically *unexpected event has happened. Or in planning his
experiment in advance, he may just want to set a halting threshold for
determining that any machine that gives him the same N consecutive numbers
in a row to be suspect. In that case, the event hasn't happened but has a
finite potential for happening and we want to detect that if it happens ...
too much.

Those "events" don't _happen_.  They simply _are_


This bit seems more philosophical than something a statistician would
likely [no pun intended] worry about. Admittedly, my choice of
words--throughout my post--could have been more precise, but I would not
have said that "events simply are."  When discussing the nature of time in
a "block universe," maybe that could be said, but I would have been in
Henri Bergson's corner [to my peril, of course] in the 1922 debate between
Bergson and Albert Einstein on the subject of time. :-) Curiously,
Bergson's idea of time is coming back--see *Time Reborn* (2013) by Lee
Smolin.  But this is likely not what you meant. However, you are an
out-of-the-closet Platonist by your own admission. No worries; I have
friends who are Platonists, most of them being mathematicians or
philosophers or believe the brain to be a computer, but not typically
computational scientists and certainly not cognitive scientists. :-) No
such thing as computational philosophy ... yet. Hmmm.

BTW, a Random Variable--continuous or 

Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[Frank Wimberly]

Don't think about choosing.  The axiom of choice says that there is a function 
from each set (subset) to an element of itself, as I recall.

Frank


Frank C. Wimberly
140 Calle Ojo Feliz
Santa Fe, NM 87505

wimber...@gmail.com wimbe...@cal.berkeley.edu
Phone:  (505) 995-8715  Cell:  (505) 670-9918

-Original Message-
From: Friam [mailto:friam-boun...@redfish.com] On Behalf Of glen ?
Sent: Wednesday, December 14, 2016 11:36 AM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] probability vs. statistics (was Re: Model of induction)


Ha!  Yay!  Yes, now I feel like we're discussing the radicality (radicalness?) 
of Platonic math ... and how weird mathematicians sound (to me) when they say 
we're discovering theorems rather than constructing them. 8^)

Perhaps it's helpful to think about the "axiom of choice"?  Is a "choosable" 
element somehow distinct from a "chosen" element?  Does the act of choosing 
change the element in some way I'm unaware of?  Does choosability require an 
agent exist and (eventually) _do_ the choosing?



On 12/14/2016 10:24 AM, Eric Charles wrote:
> Ack! Well... I guess now we're in the muck of what the heck probability and 
> statistics are for mathematicians vs. scientists. Of note, my understanding 
> is that statistics was a field for at least a few decades before it was 
> specified in a formal enough way to be invited into the hallows of 
> mathematics departments, and that it is still frequently viewed with 
> suspicion there.
> 
> Glen states: /We talk of "selecting" or "choosing" subsets or elements 
> from larger sets.  But such "selection" isn't an action in time.  Such 
> "selection" is an already extant property of that organization of 
> sets./
> 
> I find such talk quite baffling. When I talk about selecting or choosing or 
> assigning, I am talking about an action in time. Often I'm talking about an 
> action that I personally performed. "You are in condition A. You are in 
> condition B. You are in condition A." etc. Maybe I flip a coin when you walk 
> into my lab room, maybe I pre-generated some random numbers, maybe I look at 
> the second hand of my watch as soon as you walk in, maybe I write down a 
> number "arbitrarily", etc. At any rate, you are not in a condition before I 
> put you in one, and whatever it is I want to measure about you hasn't 
> happened yet.
> 
> I fully admit that we can model the system without reference to time, 
> if we want to. Such efforts might yield keen insights. If Glen had 
> said that we can usefully model what we are interested in as an 
> organized set with such-and-such properties, and time no where to be 
> found, that might seem pretty reasonable. But that would be a formal 
> model produced for specific purposes, not the actual phenomenon of 
> interest. Everything interesting that we want to describe as 
> "probable" and all the conclusions we want to come to "statistically" 
> are, for the lab scientist, time dependent phenomena. (I assert.)

--
☣ glen


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Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[Grant Holland]

And I completely agree with Eric. But we can language it real simply and 
intuitively by just looking at what a probability space is. For further 
simplicity lets keep it to a finite probability space. (Neither a finite 
nor an infinite one says anything about "time".)


A finite probability space has 3 elements: 1) a set of sample points 
called "the sample space", 2) a set of events, and 3) a set of 
probabilities /for the events/. (An infinite probability space is 
strongly similar.)


But what is this "set of events"? That's the question that is being 
discussed on this thread. It turns out that the events for a finite 
space is nothing more than /the set of all possible combinations of the 
sample points/. (Formally the event set is something called a "sigma 
algebra", but no matter.) So, an event scan be thought of simply /all 
//combination//s of the sample points/.


Notice that it is the events that have probabilities - not the sample 
points. Of course it turns out that each of the sample points happens to 
be a  (trivial) combination of the sample space - therefore it has a 
probability too!


So, the events already /have/ probabilities by virtue of just being in a 
probability space. They don't have to be "selected", "chosen" or any 
such thing. They "just sit there" and have probabilities - all of them. 
The notion of time is never mentioned or required.


Admittedly, this formal (mathematical) definition of "event" is not 
equivalent to the one that you will find in everyday usage. The everyday 
one /does/ involve time. So you could say that everyday usage of "event" 
is "an application" of the formal "event" used in probability theory. 
This confusion between the everyday "event" and the formal "event" may 
be the root of the issue.


Jus' sayin'.

Grant


On 12/14/16 11:36 AM, glen ☣ wrote:

Ha!  Yay!  Yes, now I feel like we're discussing the radicality (radicalness?) 
of Platonic math ... and how weird mathematicians sound (to me) when they say 
we're discovering theorems rather than constructing them. 8^)

Perhaps it's helpful to think about the "axiom of choice"?  Is a "choosable" element 
somehow distinct from a "chosen" element?  Does the act of choosing change the element in some way 
I'm unaware of?  Does choosability require an agent exist and (eventually) _do_ the choosing?



On 12/14/2016 10:24 AM, Eric Charles wrote:

Ack! Well... I guess now we're in the muck of what the heck probability and 
statistics are for mathematicians vs. scientists. Of note, my understanding is 
that statistics was a field for at least a few decades before it was specified 
in a formal enough way to be invited into the hallows of mathematics 
departments, and that it is still frequently viewed with suspicion there.

Glen states: /We talk of "selecting" or "choosing" subsets or elements from larger sets.  But such 
"selection" isn't an action in time.  Such "selection" is an already extant property of that 
organization of sets./

I find such talk quite baffling. When I talk about selecting or choosing or assigning, I am talking 
about an action in time. Often I'm talking about an action that I personally performed. "You 
are in condition A. You are in condition B. You are in condition A." etc. Maybe I flip a coin 
when you walk into my lab room, maybe I pre-generated some random numbers, maybe I look at the 
second hand of my watch as soon as you walk in, maybe I write down a number 
"arbitrarily", etc. At any rate, you are not in a condition before I put you in one, and 
whatever it is I want to measure about you hasn't happened yet.

I fully admit that we can model the system without reference to time, if we want to. Such efforts 
might yield keen insights. If Glen had said that we can usefully model what we are interested in as 
an organized set with such-and-such properties, and time no where to be found, that might seem 
pretty reasonable. But that would be a formal model produced for specific purposes, not the actual 
phenomenon of interest. Everything interesting that we want to describe as "probable" and 
all the conclusions we want to come to "statistically" are, for the lab scientist, time 
dependent phenomena. (I assert.)



FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[glen ☣]

Ha!  Yay!  Yes, now I feel like we're discussing the radicality (radicalness?) 
of Platonic math ... and how weird mathematicians sound (to me) when they say 
we're discovering theorems rather than constructing them. 8^)

Perhaps it's helpful to think about the "axiom of choice"?  Is a "choosable" 
element somehow distinct from a "chosen" element?  Does the act of choosing 
change the element in some way I'm unaware of?  Does choosability require an 
agent exist and (eventually) _do_ the choosing?



On 12/14/2016 10:24 AM, Eric Charles wrote:
> Ack! Well... I guess now we're in the muck of what the heck probability and 
> statistics are for mathematicians vs. scientists. Of note, my understanding 
> is that statistics was a field for at least a few decades before it was 
> specified in a formal enough way to be invited into the hallows of 
> mathematics departments, and that it is still frequently viewed with 
> suspicion there.
> 
> Glen states: /We talk of "selecting" or "choosing" subsets or elements from 
> larger sets.  But such "selection" isn't an action in time.  Such "selection" 
> is an already extant property of that organization of sets./
> 
> I find such talk quite baffling. When I talk about selecting or choosing or 
> assigning, I am talking about an action in time. Often I'm talking about an 
> action that I personally performed. "You are in condition A. You are in 
> condition B. You are in condition A." etc. Maybe I flip a coin when you walk 
> into my lab room, maybe I pre-generated some random numbers, maybe I look at 
> the second hand of my watch as soon as you walk in, maybe I write down a 
> number "arbitrarily", etc. At any rate, you are not in a condition before I 
> put you in one, and whatever it is I want to measure about you hasn't 
> happened yet.
> 
> I fully admit that we can model the system without reference to time, if we 
> want to. Such efforts might yield keen insights. If Glen had said that we can 
> usefully model what we are interested in as an organized set with 
> such-and-such properties, and time no where to be found, that might seem 
> pretty reasonable. But that would be a formal model produced for specific 
> purposes, not the actual phenomenon of interest. Everything interesting that 
> we want to describe as "probable" and all the conclusions we want to come to 
> "statistically" are, for the lab scientist, time dependent phenomena. (I 
> assert.)

-- 
☣ glen


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Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[Eric Charles]

Ack! Well... I guess now we're in the muck of what the heck probability and
statistics are for mathematicians vs. scientists. Of note, my understanding
is that statistics was a field for at least a few decades before it was
specified in a formal enough way to be invited into the hallows of
mathematics departments, and that it is still frequently viewed with
suspicion there.

Glen states: *We talk of "selecting" or "choosing" subsets or elements from
larger sets.  But such "selection" isn't an action in time.  Such
"selection" is an already extant property of that organization of sets.*

I find such talk quite baffling. When I talk about selecting or choosing or
assigning, I am talking about an action in time. Often I'm talking about an
action that I personally performed. "You are in condition A. You are in
condition B. You are in condition A." etc. Maybe I flip a coin when you
walk into my lab room, maybe I pre-generated some random numbers, maybe I
look at the second hand of my watch as soon as you walk in, maybe I write
down a number "arbitrarily", etc. At any rate, you are not in a condition
before I put you in one, and whatever it is I want to measure about you
hasn't happened yet.

I fully admit that we can model the system without reference to time, if we
want to. Such efforts might yield keen insights. If Glen had said that we
can usefully model what we are interested in as an organized set with
such-and-such properties, and time no where to be found, that might seem
pretty reasonable. But that would be a formal model produced for specific
purposes, not the actual phenomenon of interest. Everything interesting
that we want to describe as "probable" and all the conclusions we want to
come to "statistically" are, for the lab scientist, time dependent
phenomena. (I assert.)



---
Eric P. Charles, Ph.D.
Supervisory Survey Statistician
U.S. Marine Corps


On Wed, Dec 14, 2016 at 12:16 PM, glen ☣  wrote:

>
> Thanks!  Everything you say seems to land squarely in my opponent's camp,
> with the focus on the concept of an action or event, requiring some sort of
> partially ordered index (like time).  But you included the clause "but
> doesn't have to be".  I'd like to hear more about what you conceive
> probability theory to be without events, actions, time, etc.
>
> For the sake of this argument, anyway, my concept is affine to Grant's:
> "the study of probability spaces".  Probability, to me, is just the study
> of the sizes of sets where all the sizes are normalized to the [0,1]
> interval.  We talk of "selecting" or "choosing" subsets or elements from
> larger sets.  But such "selection" isn't an action in time.  Such
> "selection" is an already extant property of that organization of sets.
> Likewise, the "events" of probability are merely analogous to the events we
> experience in subjective time.  Those "events" are (various) properties or
> predicates that hold over whatever set of sets is under consideration.
> Those "events" don't _happen_.  They simply _are_.
>
> Since your language seems to depend on the idea that those predicates must
> _happen_ (i.e. at one point, they are potential or imaginary, and the next
> they are actual or factual), yet you say they don't have to, I'd like to
> hear you explain how "they don't have to".  What are these "events" absent
> time (or another such partially ordered index)?
>
> p.s. FWIW, I have the same problem with the concept of "function" and
> asymmetric transformations.  I accept the idea of a non-invertible
> function.  But by accepting that, am I forced to admit something like
> time?  Or, asked another way: As all the no-go theorem provers keep telling
> us (Tarski, Gödel, Wolpert, Arrow, ...), are we doomed to a "turtles all
> the way down" perspective?
>
>
> On 12/13/2016 05:03 PM, Robert Wall wrote:
> > At the risk of exposing my own ignorance, I'll also say your question
> has to do with the ontological status of any random "event" when treated in
> any estimation experiments or likelihood computation; that is, are proposed
> probability events or measured statistical events real?
> >
> > For example--examples are always good to help clarify the question--is
> the likelihood of a lung cancer event given a history of smoking pointing
> to some reality that will actually occur with a certain amount of
> uncertainty? In a population of smokers, yes.  For an individual smoker,
> no. In the language of probability and statistics, we say that in a
> population of smokers we /expect /this reality to be observed with a
> certain amount of certainty (probability). To be sure, these tests would
> likely involve several levels of contingencies to tame troublesome
> confounding variables (e.g., age, length of time, smoking rate). Don't want
> to get into multi-variate statistics, though.
> >
> > Obviously, time is involved here but doesn't have to be (e.g., the
> probability of drawing four aces from a 

Re: [FRIAM] (amused): Re: Spam solutions

[Gillian Densmore]

Yeah. I think the blurbs I read talk sugested them. YAR!

Their was some other company I can't remember the name of sugested in my
search. They're working with google somehow so as Google-Voice works with
them somehow. One part of the issue is these guys (illegally) use fake
names and numbers.
The (potentially) kind of cool side effect of that is trying to get some
sanity and 'just works' with phones and internet. Their's a bunch of ideas
and (alpha) tools roaming around. One was inspired by star trek's 'hailing'
frequency system. From what I gather seeing if ol'fationed landlines can
somehow talk to the cloud. Admitedly I read that after having a little
nyquil as I've got a low grade bug.  I might simply be wrong or misread the
blurb on Tech Republic.


On Tue, Dec 13, 2016 at 7:57 PM, Edward Angel  wrote:

> Check out nomorobo.com. It’s free on landlines if the carrier supports
> it. Small monthly charge for cell phones. We have it since we have a
> comcast digital phone at home. It captures almost 100% of the robo calls.
> If one gets through, we can add the number to their data base. Only one
> every couple of weeks gets through. The way it works is that the phone
> rings both at home and on their computer (big potential security issue).
> Between the first and second rings, they look up the number in their data
> base and if it’s in there, they answer and we never get a second ring.
>
> Ed
> ___
>
> Ed Angel
>
> Founding Director, Art, Research, Technology and Science Laboratory
> (ARTS Lab)
> Professor Emeritus of Computer Science, University of New Mexico
>
> 1017 Sierra Pinon
> Santa Fe, NM 87501
> 505-984-0136 <(505)%20984-0136> (home)   an...@cs.unm.edu
> 505-453-4944 <(505)%20453-4944> (cell)  http://www.cs.unm.edu/~angel
>
> On Dec 13, 2016, at 7:42 PM, Gillian Densmore 
> wrote:
>
> Having about enough of Borg Callers (Robo dialers or equivilant) googled
> to see what the heck can be done?
> This cam about when I found my voice mail (landline) could in about 4-5
> days fill up from assorted  800 numbers calling and hanging up.
> Wanting to do somthing about that I googled and  came across several
> amusing and frighting facts. Such as of the 60-65 unique area codes in
> america  about 10-15 have an enormous number of there phone numbers used up
> by  essently fake companies to spam people.
> Then
> I came across articles like this:
>
> http://www.cbsnews.com/news/8-tips-to-stop-annoying-robocalls/
>
> A few other simillar articles say basically: Make sure your on the do not
> call list, don't bother answering, if your phone supports it block it etc.
>
>
> The cool (and oddly disturbing part)
> Almost all the comments say:
> -Try Google voice as your main number Google has a low tollerance for
> aholery
> -Report any spam to google as spam who (supposedly)  eventually just
> blocks numbers automatically.
> -LOUD Music or Noises close to the phone somehow breaks the robodialers so
> they just wont call.
>
>
> For What it's Worth my experience has been Google Voice seems average for
> automagic 800 screening. They howevr realy kick butt when you report
> numbers as spam.
>
> I'm also amused coments sugesting loud drumming music (like scotland the
> brave, the 1812 overature, or Taiko drumming) to stop robo callers on your
> land line.
> 
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>
>
> 
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Re: [FRIAM] probability vs. statistics (was Re: Model of induction)

[glen ☣]

Thanks!  Everything you say seems to land squarely in my opponent's camp, with 
the focus on the concept of an action or event, requiring some sort of 
partially ordered index (like time).  But you included the clause "but doesn't 
have to be".  I'd like to hear more about what you conceive probability theory 
to be without events, actions, time, etc.

For the sake of this argument, anyway, my concept is affine to Grant's: "the 
study of probability spaces".  Probability, to me, is just the study of the 
sizes of sets where all the sizes are normalized to the [0,1] interval.  We 
talk of "selecting" or "choosing" subsets or elements from larger sets.  But 
such "selection" isn't an action in time.  Such "selection" is an already 
extant property of that organization of sets.  Likewise, the "events" of 
probability are merely analogous to the events we experience in subjective 
time.  Those "events" are (various) properties or predicates that hold over 
whatever set of sets is under consideration.  Those "events" don't _happen_.  
They simply _are_.

Since your language seems to depend on the idea that those predicates must 
_happen_ (i.e. at one point, they are potential or imaginary, and the next they 
are actual or factual), yet you say they don't have to, I'd like to hear you 
explain how "they don't have to".  What are these "events" absent time (or 
another such partially ordered index)?

p.s. FWIW, I have the same problem with the concept of "function" and 
asymmetric transformations.  I accept the idea of a non-invertible function.  
But by accepting that, am I forced to admit something like time?  Or, asked 
another way: As all the no-go theorem provers keep telling us (Tarski, Gödel, 
Wolpert, Arrow, ...), are we doomed to a "turtles all the way down" perspective?


On 12/13/2016 05:03 PM, Robert Wall wrote:
> At the risk of exposing my own ignorance, I'll also say your question has to 
> do with the ontological status of any random "event" when treated in any 
> estimation experiments or likelihood computation; that is, are proposed 
> probability events or measured statistical events real? 
> 
> For example--examples are always good to help clarify the question--is the 
> likelihood of a lung cancer event given a history of smoking pointing to some 
> reality that will actually occur with a certain amount of uncertainty? In a 
> population of smokers, yes.  For an individual smoker, no. In the language of 
> probability and statistics, we say that in a population of smokers we /expect 
> /this reality to be observed with a certain amount of certainty 
> (probability). To be sure, these tests would likely involve several levels of 
> contingencies to tame troublesome confounding variables (e.g., age, length of 
> time, smoking rate). Don't want to get into multi-variate statistics, though. 
> 
> Obviously, time is involved here but doesn't have to be (e.g., the 
> probability of drawing four aces from a trial of five random draws). An event 
> is an observation in, say, a nonparametric Fisher exact test of significance 
> against the null hypothesis of, say, a person that smokes will contract lung 
> cancer, which we can make contingent on, say, the number of years of smoking. 
> Epidemiological studies can be very complex, so maybe not the best of 
> examples ...
> 
> So, since probability and statistics both deal with the idea of an event--as 
> your "opponent" insists--events are just observations that the event of 
> interest [e.g., four of a kind] occurred; so I would say epistemologically 
> they are real experiences with a potential (probability) based on either 
> controlled randomized experiments of observational experience.  But is a 
> potential ontologically real?  樂
> 
> Asking if those events come with ontologically real probabilistic properties 
> is another, perhaps, different question?  This gets into worldview notions of 
> determinism and randomness. We tend to say that if a human cannot predict the 
> event in advance, it is random ... enough. If it can be predicted based, say, 
> on known initial conditions, then using probability theory here is misplaced. 
> Still, there are chaotic non-random events that are not practically 
> predictable ... they seem random ... enough.  Santa Fe science writer and 
> book author George Johnson gets into this in his book /Fire in the Mind/.

-- 
☣ glen


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Re: [FRIAM] Model of induction

[Owen Densmore]

All three (Aaron Clauset and Cosma R. Shalizi and Mark E. J. Newman) have
given great courses at the SFI summer school.

On Tue, Dec 13, 2016 at 8:41 PM, Nick Thompson 
wrote:

> Hi, Russell S.,
>
> It's a long time since the old days of the Three Russell's, isn't it?
> Where have all the Russell's gone?  Good to hear from you.
>
> This has been a humbling experience.  My brother was a mathematician and
> he used to frown every time asked him what I thought was a simple
> mathematical question.
>
> So ... with my heart in my hands ... please tell me, why a string of 100
> one's , followed by a string of 100 2's, ..., followed by a string of 100
> zero's wouldn’t be regarded as random.  There must be something more than
> uniform distribution, eh?
>
> Is there a halting problem lurking here?
>
> Nick
>
> Nicholas S. Thompson
> Emeritus Professor of Psychology and Biology
> Clark University
> http://home.earthlink.net/~nickthompson/naturaldesigns/
>
> -Original Message-
> From: Friam [mailto:friam-boun...@redfish.com] On Behalf Of Russell
> Standish
> Sent: Tuesday, December 13, 2016 7:59 PM
> To: 'The Friday Morning Applied Complexity Coffee Group' <
> friam@redfish.com>
> Subject: Re: [FRIAM] Model of induction
>
> On Mon, Dec 12, 2016 at 02:45:11PM -0700, Nick Thompson wrote:
> >
> >
> > Let’s take out all the colorful stuff and try again.  Imagine a thousand
> computers, each generating a list of random numbers.  Now imagine that for
> some small quantity of these computers, the numbers generated are in n a
> normal (Poisson?) distribution with mean mu and standard deviation s.  Now,
> the problem is how to detect these non-random computers and estimate the
> values of mu and s.
> >
>
> Your question comes down to: given a set of statistical distributions (ie
> models), which model best fits a given data source. In your case,
> presumably you have two models - a uniform distribution and a normal (or
> Poisson - they're two different distibutions resulting from additive versus
> multiplicative processes respectively) distribution.
>
> The paper to read on this topic is
>
> @Article{Clauset-etal07,
>   author =   {Aaron Clauset and Cosma R. Shalizi and Mark E. J.
> Newman},
>   title ={Power-law Distributions in Empirical Data},
>   journal =  {SIAM Review},
>   volume = 51,
>   pages = {661-703},
>   year = 2009,
>   note = {arXiv:0706.1062}
> }
>
> Almost everyone doing work in Complex Systems theory with power laws has
> been doing it wrong! The way it should be done is to compare a metric
> called "likelihood" calculated over the data and a model, for the different
> models in question.
>
> I was scheduled to give a talk "Perils of Power Laws" at a local Complex
> Systems conference in 2007. Originally, when I proposed the topic, I
> planned to synthesise and collect some of my war stories relating to power
> law problems - but a couple of months before the conference, someone showed
> me Clauset's paper. I was so impressed by it, not only superseding anything
> I could do on the timescale, but also I felt was so important for my
> colleagues to know about that I took the unprecedented step of presenting
> someone else's paper at the conference. With full attribution, of course. I
> still feel it was the most important paper in my field of 2007, and one of
> the most important papers of this century. Even though it didn't officially
> get published until 2009 :).
>
> Nick's question is unrelated to the question of how to detect whether a
> source is random or not. A non-uniform random source is one that can be
> transformed into a uniform random source by a computable transformation, so
> uniformity is not really a test of randomness.
>
> Detecting whether a source is random or not is not a computational
> feasible task. All one can do is prove that a given source is non-random
> (by providing an effective generator of the data), but you can never prove
> a source is truly random, except by exhaustive testing of all Turing
> machines less than the data's complexity, which suffers from combinatoric
> computational complexity.
>
> Cheers
>
> --
>
> 
> 
> Dr Russell StandishPhone 0425 253119 (mobile)
> Principal, High Performance Coders
> Visiting Senior Research Fellowhpco...@hpcoders.com.au
> Economics, Kingston University http://www.hpcoders.com.au
> 
> 
>
> 
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[FRIAM] 55 Conversations Later, Here’s What Our Data-And-Society Podcast Taught Me | FiveThirtyEight

[Tom Johnson]

http://fivethirtyeight.com/features/55-conversations-later-heres-what-our-data-and-society-podcast-taught-me/

Some topics here you may find of interest.  Perhaps we should livestream
the Friday morning sessions.  Well, some and even just parts of that.

Tom (in Kuala Lumpur, soon headed to Penang until Jan. 9, should anyone be
in the area)

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