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<DIV>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">Pavel, Joel, Paul, and Eshel—</P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"> </P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">See if I’ve understood the
following article correctly.<SPAN style="mso-spacerun: yes"> </SPAN></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">In this cosmos things don’t
follow the sort of random spread of probabilities Ludwig Boltzmann believed
in.<SPAN style="mso-spacerun: yes"> </SPAN>Instead, old patterns jump from
one level to another, showing up in new news.<SPAN
style="mso-spacerun: yes"> </SPAN></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">To understand the size and nature
of the jumps, we have to understand something even deeper—the search strategies
with which the cosmos explores what Stuart Kaufman calls “possibility
space”.</P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">The key quote from the article
below is this one:<SPAN style="mso-spacerun: yes"> </SPAN>“<B
style="mso-bidi-font-weight: normal"><SPAN
style="BACKGROUND: yellow; mso-highlight: yellow">if physicists can adequately
understand the details of this ‘exploring behaviour’, they should be able to
predict values of q from first principles</SPAN>”.</B></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">Now please bear with me.<SPAN
style="mso-spacerun: yes"> </SPAN>What I’ve been digging into for many
decades is the manner in which the cosmos feels out her possibilities—the search
strategies of nature. So have Eshel Ben-Jacob, Paul Werbos, Pavel Kurakin, and
Joel Isaacson. <SPAN style="mso-spacerun: yes"> </SPAN></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">Pavel and I, in our paper
“Conversation (dialog) model of quantum transitions” (arXiv.org) suggest that we
may find applications all up and down the scale of nature to one search strategy
in particular, that used by a cloud of 20,000 smart particles—bees.</P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">Power laws help us move from the
human-scale to the very big.<SPAN style="mso-spacerun: yes"> </SPAN>They
help us understand how patterns visible on one scale—the scale of the spiral of
water that flushes your toilet, for example, can be scaled up to hurricanes, to
vortex of the Red Spot on the surface of Jupiter, to hurricanes on Jupiter the
size of thirty earths, and to the spirals of billions of stars called
galaxies.<SPAN style="mso-spacerun: yes"> </SPAN>Power laws or their
equivalent also allow us to predict that if we give the cosmos another six or
seven billion years, the spirals from your toilet will show up in swirls of
multitudes of galaxies—they will show up in today’s potato-shaped,
still-embryonic galaxy clusters.<SPAN style="mso-spacerun: yes">
</SPAN></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">Power laws can be used in forward
or reverse.<SPAN style="mso-spacerun: yes"> </SPAN>In addition to going
from the small to the very big, they can help us move from the human-scale to
the very small.<SPAN style="mso-spacerun: yes"> </SPAN>Power laws help us
understand how the swirl in your bathtub shows up in the swizzles of electrons
twisting through a channel on a superconductor.<SPAN
style="mso-spacerun: yes"> </SPAN></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">On the level of life, we can see
search patterns at work, search patterns in Dennis Bray’s clusters of receptors
on a cell wall, search patterns in Eshel Ben-Jacobs multi-trillion-member
bacterial colonies, search patterns in Tom Seeley’s colonies of bees, search
patterns in E.O. Wilson’s colonies of ants, and search patterns in colonies of
termites.<SPAN style="mso-spacerun: yes"> </SPAN>We can see search
patterns in the motions of birds, and in the way these patterns have been
modeled mathematically in Floys (mathematically-generated flocks of carnivorous
Boids—see http://www.aridolan.com/ofiles/JavaFloys.html). We can see search
patterns in Martha Sherwood’s vampire bats, and search patterns in the areas of
my fieldwork--human cultural fads and fashions and the multi-generational search
patterns of art, religion, ideology, world-views, and science.</P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">If search patterns are the key to
understanding the factor q, if they are the key to comprehending the magic
factor that scales things up and down in giant, discontinuous leaps, then let’s
by all means take search patterns at the scale of life and apply them like
hell.</P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">That’s exactly what Pavel Kurakin
and I have done in our paper.<SPAN style="mso-spacerun: yes"> </SPAN>And
it’s what I’ve done in much of my work, including in a book that’s been growing
in the Bloom computer for fifteen years-- A Universe In Search Of Herself—The
Case of the Curious Cosmos.</P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">Now the question is this.<SPAN
style="mso-spacerun: yes"> </SPAN>Have I misinterpreted the material
below?<SPAN style="mso-spacerun: yes"> </SPAN>And even if I’ve mangled it
utterly, could an understanding of search patterns at one scale in the cosmos
echo the patterns at other levels big and small?<SPAN
style="mso-spacerun: yes"> </SPAN>If the search patterns of life are
reflected in the inanimate cosmos, do the search patterns of life in turn
reflect the search patterns of the particles and processes of which they are
made?<SPAN style="mso-spacerun: yes"> </SPAN>And do the search patterns of
an organism reflect the search patterns of her flock, her tribe, her culture,
and of the total team of biomass?<SPAN style="mso-spacerun: yes">
</SPAN></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">To what extent are competing
search patterns a part of the cosmic process?<SPAN
style="mso-spacerun: yes"> </SPAN>Did competing search patterns only show
up 3.85 billion years ago with the advent of life (assuming that the advent of
life on earth took place at the same time as the advent of life—if there is
any—elsewhere in the universe)?<SPAN style="mso-spacerun: yes"> </SPAN>Are
the gaps between competing search patterns also big ones, with their own chasms
and jumps spaced out by their own mysterious q?</P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">Biomass has been probing this
planet for 3.85 billion years now, and we are the fingers with which she feels
out her possibilities.<SPAN style="mso-spacerun: yes"> </SPAN>But we are
also the fingers through which social clusters of protons 13.7 billion years old
feel out their future.<SPAN style="mso-spacerun: yes"> </SPAN>Is q related
to the discipline of a probing strategy?<o:p></o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=MsoNormal style="MARGIN: 0in 0in 0pt">Retrieved <SPAN
style="mso-no-proof: yes">August 31, 2005</SPAN>, from the World Wide Web<SPAN
style="mso-spacerun: yes">
</SPAN>http://www.newscientist.com/channel/fundamentals/mg18725141.700
NewScientist.com<SPAN style="mso-spacerun: yes"> </SPAN>* HOME * |NEWS *
|EXPLORE BY SUBJECT * |LAST WORD * |SUBSCRIBE * |SEARCH * |ARCHIVE * |RSS *
|JOBS<SPAN style="mso-spacerun: yes"> </SPAN>Click to Print Entropy: The
new order<SPAN style="mso-spacerun: yes"> </SPAN>* <st1:date Month="8"
Day="27" Year="2005">27 August 2005</st1:date> * From New Scientist Print
Edition. Subscribe and get 4 free issues. * Mark Buchanan<SPAN
style="mso-spacerun: yes"> </SPAN><B
style="mso-bidi-font-weight: normal">CONSTANTINO TSALLIS has a single
equation</B> written on the blackboard in his office. It looks like one of the
most famous equations in physics, but look more closely and it's a little bit
different, decorated with some extra symbols and warped into a peculiar new
form.<SPAN style="mso-spacerun: yes"> </SPAN>Tsallis, based at the
Brazilian Centre for Research in Physics, <st1:City><st1:place>Rio de
Janeiro</st1:place></st1:City>, is excited to have created this new equation.
And no wonder: his unassuming arrangement of symbols <B
style="mso-bidi-font-weight: normal">has stimulated hundreds of researchers to
publish more than a thousand papers in the past decade, describing strange
patterns in fluid flows, in magnetic fields issuing from the sun and in the
subatomic debris created in particle accelerators.</B> But there is something
even more remarkable about <B style="mso-bidi-font-weight: normal">Tsallis's
equation: it came to him in a daydream.</B><SPAN
style="mso-spacerun: yes"> </SPAN>In 1985, in a classroom in
<st1:City><st1:place>Mexico City</st1:place></st1:City>, Tsallis was listening
as a colleague explained something to a student. On the chalkboard they had
written a very ordinary algebraic expression, pq, representing some number p
raised to the power q In Tsallis's line of work - describing the collective
properties of large numbers of particles - the letter "p" usually stands for
probability: the probability that a particle will have a particular velocity,
say. Tsallis stared at the formula from a distance and his mind drifted off.
"There were these pqs all over the board," he recalls, "and it suddenly came to
my mind - like a flash - that with powers of probabilities one might do some
unusual but possibly quite interesting physics."<SPAN
style="mso-spacerun: yes"> </SPAN>The physics involved may be more than
quite interesting, however. <B style="mso-bidi-font-weight: normal">The standard
means of describing the collective properties of large numbers of particles -
known as statistical mechanics</B> - has been hugely successful for more than a
century, but it has also been rather limited in its scope: you can only apply it
to a narrow range of systems. Now, with an insight plucked out of thin air,
Tsallis may have changed all that. <B style="mso-bidi-font-weight: normal"><SPAN
style="mso-spacerun: yes"> </SPAN>Developed in the 19th century,
statistical mechanics enabled physicists to overcome an imposing problem.
Ordinary materials such as water, iron or glass are made of myriad atoms. But
since it is impossible to calculate in perfect detail how every individual atom
or molecule will move, it seems as if it might never be possible to understand
the behaviour of such substances at the atomic level.<SPAN
style="mso-spacerun: yes"> </SPAN>The solution, as first suggested by the
Austrian physicist Ludwig Boltzmann, lay in giving up hope of perfect
understanding and working with probabilities instead. Boltzmann argued that
knowing the probabilities for the particles to be in any of their various
possible configurations would enable someone to work out the overall properties
of the system. Going one step further, he also made a bold and insightful guess
about these probabilities - that any of the many conceivable configurations for
the particles would be equally probable.</B> Deeper beauty<SPAN
style="mso-spacerun: yes"> </SPAN>Boltzmann's idea works, and has enabled
physicists to make mathematical models of thousands of real materials, from
simple crystals to superconductors. But his work also has a deeper beauty. For a
start, it reflects the fact that many quantities in nature - such as the
velocities of molecules in a gas - follow "normal" statistics. That is, they are
closely grouped around the average value, with a "bell curve" distribution.<SPAN
style="mso-spacerun: yes"> </SPAN><B
style="mso-bidi-font-weight: normal">The theory also explains why, if left to
their own devices, systems tend to get disorganised. Boltzmann argued that any
system that can be in several different configurations is most likely to be in
the more spread out and disorganised condition.</B> Air molecules in a box, for
example, can gather neatly in a corner, but are more likely to fill the space
evenly. <B style="mso-bidi-font-weight: normal">That's because there are
overwhelmingly more arrangements of the particles that will produce the spread
out, jumbled state than arrangements that will concentrate the molecules in a
corner. This way of thinking led to the famous notion of entropy</B> - a measure
of the amount of disorder in a system. In its most elegant formulation, <B
style="mso-bidi-font-weight: normal">Boltzmann's statistical mechanics, which
was later developed mathematically by the American physicist Josiah Willard
Gibbs, asserts that, under many conditions, a physical system will act so as to
maximise its entropy.</B><SPAN style="mso-spacerun: yes"> </SPAN>And yet
Boltzmann and Gibbs's statistical mechanics doesn't explain everything: a great
swathe of nature eludes its grasp entirely. Boltzmann's guess about equal
probabilities only works for systems that have settled down to equilibrium,
enjoying, for example, the same temperature throughout. <B
style="mso-bidi-font-weight: normal">The theory fails in any system where
destabilising external sources of energy are at work, such as the haphazard
motion of turbulent fluids or the fluctuating energies of cosmic rays.</B> These
systems don't follow normal statistics, but another pattern instead.<SPAN
style="mso-spacerun: yes"> </SPAN><B
style="mso-bidi-font-weight: normal">If you repeatedly measure the difference in
fluid velocity at two distinct points in a turbulent fluid, for instance, the
probability of finding a particular velocity difference is roughly proportional
to the amount of that difference raised to the power of some exponent. This
pattern is known as a "power law", and such patterns turn up in many other areas
of physics, from the distribution of energies of cosmic rays to the fluctuations
of river levels or wind speeds over a desert. Because ordinary statistical
mechanics doesn't explain power laws, their atomic-level origins remain largely
mysterious,</B> which is why many physicists find Tsallis's mathematics so
enticing.<SPAN style="mso-spacerun: yes"> </SPAN><B
style="mso-bidi-font-weight: normal">In </B><st1:City><st1:place><B
style="mso-bidi-font-weight: normal">Mexico City</B></st1:place></st1:City><B
style="mso-bidi-font-weight: normal">, coming out of his reverie, Tsallis
wrote</B> up some notes on his idea, and soon came to a formula that looked
something like the standard formula for the Boltzmann-Gibbs entropy - but with a
subtle difference. <B style="mso-bidi-font-weight: normal">If he set q to 1 in
the formula - so that pq became the probability p - the new formula reduced to
the old one. But if q was not equal to 1,</B> it made the formula produce
something else. <B style="mso-bidi-font-weight: normal">This led Tsallis to a
new definition of entropy. He called it q entropy.</B><SPAN
style="mso-spacerun: yes"> </SPAN>Back then, Tsallis had no idea what q
might actually signify, but the way this new entropy worked mathematically
suggested he might be on to something. In particular, <B
style="mso-bidi-font-weight: normal">the power-law pattern tumbles out of the
theory quite naturally. Over the past decade, researchers have shown that
Tsallis's mathematics seem to describe power-law behaviour accurately in a wide
range of phenomena, from fluid turbulence to the debris created in the
collisions of high-energy particles.</B> But while the idea of maximising q
entropy seems to work empirically, allowing people to fit their data to
power-law curves and come up with a value of q for individual systems, it has
also landed Tsallis in some hot water. The new mathematics seems to work, <B
style="mso-bidi-font-weight: normal">yet no one knows what the q entropy really
represents, or why any physical system should maximise it.</B> Degrees of
chaos<SPAN style="mso-spacerun: yes"> </SPAN>And for this reason, many
physicists remain sceptical, or worse. "I have to say that I don't buy it at
all," says physicist Cosma Shalizi of the
<st1:place><st1:PlaceType>University</st1:PlaceType> of
<st1:PlaceName>Michigan</st1:PlaceName></st1:place> in <st1:City><st1:place>Ann
Arbor</st1:place></st1:City>, who criticises the mathematical foundations of
Tsallis's approach. As he points out, <B
style="mso-bidi-font-weight: normal">the usual Boltzmann procedure for
maximising the entropy in statistical mechanics assumes a fixed value for the
average energy of a system, a natural idea. But to make things work out within
the Tsallis framework, researchers have to fix the value of another quantity - a
"generalised" energy - that has no clear physical interpretation. </B>"I have
yet to encounter anyone," says Shalizi, "who can explain why this should be
natural."<SPAN style="mso-spacerun: yes"> </SPAN>To his critics, Tsallis's
success is little more than sleight of hand: the equation may simply provide a
convenient way to generate power laws, which researchers can then fit to data by
choosing the right value of q "My impression," says Guido Caldarelli of La
Sapienza University in Rome, "is that the method really just fits data by
adjusting a parameter. I'm not yet convinced there's new physics here."
Physicist Peter Grassberger of the
<st1:place><st1:PlaceType>University</st1:PlaceType> of
<st1:PlaceName>Wuppertal</st1:PlaceName></st1:place> in
<st1:country-region><st1:place>Germany</st1:place></st1:country-region> goes
further. "It is all nonsense," he says. "It has led to no new predictions, nor
is it based on rational arguments."<SPAN style="mso-spacerun: yes">
</SPAN>The problem is that most work applying Tsallis's ideas has simply chosen
a value of q to make the theory fit empirical data, without tying q to the real
dynamics of the system in any deeper way: there's nothing to show why these
dynamics depart from Boltzmann's picture of equal probabilities. Tsallis, who is
now at the Santa Fe Institute in <st1:State><st1:place>New
Mexico</st1:place></st1:State>, acknowledges this is a limitation, but suggests
that a more fundamental explanation is already on its way.<SPAN
style="mso-spacerun: yes"> </SPAN><B
style="mso-bidi-font-weight: normal">Power laws, he argues, should tend to arise
in "weakly chaotic" systems. In this kind of system, small perturbations might
not be enough to alter the arrangement of molecules. As a result, the system
won't "explore" all possible configurations over time. In a properly chaotic
system, on the other hand, even tiny perturbations will keep sending the system
into new configurations, allowing it to explore all its states as required for
Boltzmann statistics.<SPAN style="mso-spacerun: yes"> </SPAN>Tsallis
argues that <SPAN style="BACKGROUND: yellow; mso-highlight: yellow">if
physicists can adequately understand the details of this "exploring behaviour",
they should be able to predict values of q from first principles</SPAN>.</B> In
particular, he proposes, some as yet unknown single parameter - closely akin to
q - should describe the degree of chaos in any system. Working out its value by
studying a system's basic dynamics would then let physicists predict the value
of q that then emerges in its statistics.<SPAN style="mso-spacerun: yes">
</SPAN>Other theoretical work seems to support this possibility. For example, in
a paper soon to appear in Physical Review E, physicist Alberto Robledo of the
National Autonomous University of Mexico in <st1:City><st1:place>Mexico
City</st1:place></st1:City> has examined several <B
style="mso-bidi-font-weight: normal">classic models that physicists have used to
explore the phenomenon of chaos.</B> What makes these models useful is that they
<B style="mso-bidi-font-weight: normal">can be tuned to be more or less
chaotic</B> - and so used to explore the transition from one kind of behaviour
to another. Using these model systems, Robledo has been able to carry out
Tsallis's prescription, deriving a value of q just from studying the system's
fundamental dynamics. That value of q then reproduces intricate power-law
properties for these systems at the threshold of chaos. "This work shows that q
can be deduced from first principles," Tsallis says.<SPAN
style="mso-spacerun: yes"> </SPAN>While Robledo has tackled theoretical
issues, other researchers have made the same point with real observations. <B
style="mso-bidi-font-weight: normal">In a paper just published, Leonard Burlaga
and Adolfo Vinas at NASA's Goddard Space Flight Center in Greenbelt, Maryland,
study fluctuations in the properties of the solar wind - the stream of charged
particles that flows outward from the sun - and show that they conform to
Tsallis's ideas.</B> They have found that the dynamics of the solar wind, as
seen in changes in its velocity and magnetic field strength, display weak chaos
of the type envisioned by Tsallis. <B
style="mso-bidi-font-weight: normal">Burlaga and Vinas have also found that the
fluctuations of the magnetic field follow power laws that fit Tsallis's
framework with q set to 1.75</B> (Physica A, vol 356, p 275).<SPAN
style="mso-spacerun: yes"> </SPAN>The chance that a more comprehensive
formulation of Tsallis's q entropy might eventually be found intrigues physicist
Ezequiel Cohen of the Rockefeller University in New York City. "I think a good
part of the establishment takes an unfair position towards Tsallis's work," he
says. "The critique that all he does is 'curve fitting' is, in my opinion,
misplaced."<SPAN style="mso-spacerun: yes"> </SPAN>Cohen has also started
building his own work on Tsallis's foundations. <B
style="mso-bidi-font-weight: normal">Two years ago, with Christian Beck of Queen
Mary, </B><st1:place><st1:PlaceType><B
style="mso-bidi-font-weight: normal">University</B></st1:PlaceType><B
style="mso-bidi-font-weight: normal"> of </B><st1:PlaceName><B
style="mso-bidi-font-weight: normal">London</B></st1:PlaceName></st1:place><B
style="mso-bidi-font-weight: normal">, he proposed an idea known as
"superstatistics" that would incorporate the statistics of both Boltzmann and
Tsallis within a larger framework.<SPAN style="mso-spacerun: yes">
</SPAN>In this work they revisited the limitation of Boltzmann's statistical
mechanics. Boltzmann's models cannot cope with any system in which external
forces churn up differences such as variations in temperature. A particle moving
through such a system would experience many temperatures for short periods and
its fluctuations would reflect an average of the ordinary Boltzmann statistics
for all those different temperatures. Cohen and Beck showed that such averaged
statistics, emerging out of the messy non-uniformity of real systems, take the
very same form as Tsallis statistics, and lead to power laws. In one striking
example, Beck showed how the distribution of the energies of cosmic rays could
emerge from random fluctuations in the temperature of the hot matter where they
were originally created.</B><SPAN style="mso-spacerun: yes"> </SPAN>Cohen
thinks that, if nothing else, Tsallis's powers of probabilities have served to
reawaken physicists to fundamental questions they have never quite answered.
After all <B style="mso-bidi-font-weight: normal">Boltzmann's idea, though
successful, was</B> also <B style="mso-bidi-font-weight: normal">based on a
guess; Albert Einstein disliked Boltzmann's arbitrary assumption of "equal
probabilities" and insisted that a proper theory of matter had to rest on a deep
understanding of the real dynamics of particles.</B><SPAN
style="mso-spacerun: yes"> </SPAN>That understanding still eludes us, but
Tsallis may have taken us closer. It is possible that, in his mysterious q
entropy, <B style="mso-bidi-font-weight: normal">Tsallis has discovered a kind
of entropy just as useful as Boltzmann's and especially suited to the real-world
systems in which the traditional theory fails.</B> "Tsallis made the first
attempt to go beyond Boltzmann," says Cohen. The door is now open for others to
follow. Close this window Printed on Thu Sep 01 <st1:time Hour="13"
Minute="17">01:17:25</st1:time> BST 2005 </P></DIV>
<DIV> </DIV>
<DIV><FONT lang=0 FAMILY="SANSSERIF" PTSIZE="10">----------<BR>Howard
Bloom<BR>Author of The Lucifer Principle: A Scientific Expedition Into the
Forces of History and Global Brain: The Evolution of Mass Mind From The Big Bang
to the 21st Century<BR>Recent Visiting Scholar-Graduate Psychology Department,
New York University; Core Faculty Member, The Graduate
Institute<BR>www.howardbloom.net<BR>www.bigbangtango.net<BR>Founder:
International Paleopsychology Project; founding board member: Epic of Evolution
Society; founding board member, The Darwin Project; founder: The Big Bang Tango
Media Lab; member: New York Academy of Sciences, American Association for the
Advancement of Science, American Psychological Society, Academy of Political
Science, Human Behavior and Evolution Society, International Society for Human
Ethology; advisory board member: Institute for Accelerating Change ; executive
editor -- New Paradigm book series.<BR>For information on The International
Paleopsychology Project, see: www.paleopsych.org<BR>for two chapters from
<BR>The Lucifer Principle: A Scientific Expedition Into the Forces of History,
see www.howardbloom.net/lucifer<BR>For information on Global Brain: The
Evolution of Mass Mind from the Big Bang to the 21st Century, see
www.howardbloom.net<BR></FONT></DIV></FONT></BODY></HTML>