Wed Blender: Stereo and Computational Photography / Videography for Cultural Preservation

[Phil Henshaw-2]

Steve,
Yes, and to keep brief, I think there are so very many clear examples of our
being clueless about the nature of the 'game' and 'commons' we are sharing
that the earlier game theory and tragedy of the commons studies were clearly
missing something.  It think what they were missing is the arts, and or
sciences, of how to read the environment in which your conception of the
game and commons are imbedded.  

You say "We simply may not understand the implications of what our
instruments are telling us in the first case and in the second case, we may
not trust the agenda of the social constructs between us and what we are
observing (see the long-running argument over whether climate change is real
or not)."  I see both are examples of trusting our models rather than using
them as open questions for the purpose of discovering the true circumstance
we're in.

Phil

> -----Original Message-----
> From: friam-bounces at redfish.com [mailto:friam-bounces at redfish.com] On
> Behalf Of Steve Smith
> Sent: Sunday, March 30, 2008 12:11 PM
> To: The Friday Morning Applied Complexity Coffee Group
> Subject: [FRIAM] Reciprocal Altruism - was: can you have 4 operating
> systems on one buss?
>
> Folks,
>
> I apologize if I missed this in an earlier part of the thread... these
> discussions are so elaborate and rich that I simply find I cannot keep
> up with them all front to back.
>
> However... this divergence of discussing bicyclist pelotons which is
> segueing into what feels like a discussion of seeking solutions to what
> is known as the "Tragedy of the Commons" has gotten my attention.
> > The canonical example is of a resource that begins with having no
> limit for
> > a small community of users with various cooperative habits for
> exploiting
> > it.  If their habits constitute a growth system, the users will
> usually know
> > only their own individual experience and have no experiential
> information
> > about the approach of that limit.  It's not clear what their best
> source of
> > information would be about it, or how they would choose what to do at
> the
> > limits.
> >
> > What kind of information might indicate the approach of common
> resource
> > limits?  How would that be different from evidence that other users
> are
> > breaking their agreements?   As independent users of natural
> resources tend
> > to have less information about, or interest in, each other's
> particular
> > needs than, say, cyclists in a peloton, how would they begin to
> renegotiate
> > their common habits when circumstances require it?
> >
> As most of us know, there has been a lot of abstract study of this in
> Game Theory as well as practical study in economics, political science,
> and evolutionary biology.
>
> The bicycle peleton seems to arise fairly directly from "reciprocal
> altruism".  While there is some cost to the riders at the head of a
> peloton in terms of simple distraction and risk of interference, in
> general the only cost they bear is relative to the others who gain an
> advantage from an emergent common resource, the air pocket behind them
> which is unexploited otherwise.   "reciprocal altruism" is an obvious
> response, each member of the peleton being motivated to contribute to
> the group as a "windbreaker" in exchange for not being ejected or
> ditched from the peleton.  As the end of the race nears, the motivation
> to "defect" increases and only those with a shared fate (members of the
> same team) are likely to maintain pelotons right up to the last minute.
>
> Phil makes good points about global optimization under local awareness.
> As our actions begin to have longer range consequences and we begin to
> exploit a larger commons (global, including earth orbit, Lagrange
> points, and the lunar surface soon enough) our awareness of the state
> of
> said commons must be expanded equally.   This also is problematic, as
> our awareness must be mediated both technologically and socially (we
> must use telescopes, remote sensors, etc. and depend on others to share
> their observations and judgements about the condition of the commons).
> When these other devices (mechanical and social) are insinuated between
> our perceptual system and the commons in question, we are at risk of
> them being miscalibrated and of our innate perceptions not being tuned
> to them.  We simply may not understand the implications of what our
> instruments are telling us in the first case and in the second case, we
> may not trust the agenda of the social constructs between us and what
> we
> are observing (see the long-running arguement over whether climate
> change is real or not).
>
> - Steve
>
> ============================================================
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> lectures, archives, unsubscribe, maps at http://www.friam.org

[Steve Smith]

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[Marcus G. Daniels]

Phil Henshaw wrote:
>> The "user negotiated solutions" reduce to the question of a shared values.
>>    
>
> Well, not as I see it.  That would be the central manager's assumption
> for setting up rules that are to be made self-consistent, and excluding the
> environment's inconsistencies from consideration.  From an inclusive view,
> though, the individual users will have different needs, interests,
> information and perceptions and that's the general problem.
For one thing, a program, or a user of a program, can make statements of
intent.

Example 1: A Linux program that monitors another can ask to keep memory
resident and also ask for a modest scheduling frequency.   It could do
this to ensure that a peer program would get most of the CPU cycles, but
on the other hand that it would be able to count on getting enough
cycles to be able to periodically send the result of the peer
calculation to some I/O device.  Say, wavelet compression of an image
taken on a satellite before it gets sent back to earth.

Example 2:  I'm leaving work and I have a job I want done by morning.  
Rather than asking for more than I need, I make the best calculation I
can of how much CPU time the job will take and look at the queue
schedule for the upcoming 12 hours.   In particular, I can look for
holes in this calendar.   Depending on what's likely to be available, I
can either ask for a giant number of processors for only an hour, or a
small number for all 12.   I have an incentive to make realistic
estimates and to fit it into whats available.
> There are lots of things that virtualization might work for, and that's
> a good way of saying it.  It still requires the global "God's eye view" of
> things that no one naturally has... though.
In the case of computer resource sharing, I don't agree.  First of all,
people know what the system is and how fast it can in-principle
operate.   When performances drops below some fraction, users will
complain or leave.  They can't complain about unfair hogging, because
that can be dealt with fairly.
Secondly, everything the computer does can be measured.  Common code
paths can be identified and compressed.   A typical computer system has
a large number of DLLs, or frameworks, or shared libraries, etc. that
represent stuff in memory that everyone shares, i.e. they name the
resource instead of copying it (shared values in some sense).   Jobs can
even be profiled and marginalized when shown to be doing wasteful
things.   A "God's eye view" can be approximated by direct measurement,
using statements of intent, and by inference from the historical
record.   Much more so than in natural systems.  

Marcus

[Russell Standish]

On Sun, Mar 30, 2008 at 10:55:01AM -0400, Phil Henshaw wrote:

>
> The canonical example is of a resource that begins with having no limit for
> a small community of users with various cooperative habits for exploiting
> it.  If their habits constitute a growth system, the users will usually know
> only their own individual experience and have no experiential information
> about the approach of that limit.  It's not clear what their best source of
> information would be about it, or how they would choose what to do at the
> limits.  
>
> What kind of information might indicate the approach of common resource
> limits?  How would that be different from evidence that other users are
> breaking their agreements?   As independent users of natural resources tend
> to have less information about, or interest in, each other's particular
> needs than, say, cyclists in a peloton, how would they begin to renegotiate
> their common habits when circumstances require it?  
>
> Phil
>

Interesting that you should have brought the tragedy of the commons
into this. I recently read a paper by Juergen Kremer
(http://www.rheinahrcampus.de/fileadmin/prof_seiten/kremer/MasterKeenEconomics.PDF)
discussing some work that Steve Keen and I have done on the theory of
the firm. In it, he mentions that our framework can be applied to the
tragedy of the commons case, and that under the same special
conditions of prefectly rational competitors and frictionless
response, a cooperative solution will emerge that exploits the commons
without overloading it. The paper is in German, but the idea is pretty
simple once you understand our theory of the firm stuff, which you can
get from my website.

Of course, real economic agents are neither rational, nor
frictionless, and in our Complex Systems '04 paper, we explore just
how much irrationality and how much friction is required to break the
Keen ("monopoly") solution (corresponding to the benevolent dictator ToC
solution) into the Cournot ("competitive") solution (corresponding to
over exploitation of the ToC).

Cheers

--

----------------------------------------------------------------------------
A/Prof Russell Standish                  Phone [phone] (mobile)
Mathematics                        
UNSW SYDNEY 2052                 hpcoder at hpcoders.com.au
Australia                                http://www.hpcoders.com.au
----------------------------------------------------------------------------

[Phil Henshaw-2]

Russell,

Yes, the German is a little slow for me, and I found no English link, so
I'll have to hope I can ask a question or two guessing the approach from
your comments.  You say that under one set of rational assumptions the
'tragedy of the commons' in which collective behavior violates individual
interests does not arise.  I don't doubt that, but note that the dilemma for
real participants is that they are each following rational assumptions of
their own making.  

As I see it, the problem for them is needing to come to discover why their
world is producing irrational responses inconsistent with their assumptions,
to look beyond everything they think they know.  How do you deal with
discovering problems that arise from outside your own model in that way?  I
use a variety of triggers for exploratory learning.  If you assume everyone
would act as if following one set of rules designed from a global
perspective, would that actually address the core problem?

I think I count three true world financial market collapses requiring sudden
Fed intervention to stave off full disintegration of the world market system
in the last 12 months, for example.  Explosively multiplying bad bets is not
good.   The management question is how to tell what sort of misbehavior
indicates that our models of reality are in need of updating in a
non-trivial way.  I think what we're running into is an impasse caused by
the fundamental problem that our models are by definition self-consistent,
but nature by definition is composed of countless independent systems that
are by definition inconsistent.  A system of independent behaviors behaves
independently from any model we could possibly make of it.  

The world we 'see with our models' may appear consistent, but that may be
only by means of our filtering the information we get accordingly, and
that's the rub.   Getting increasing signals that we're crossing lines of
conflict with the world outside our models, in any number of directions all
at once, seems to me to suggest we should 'look around' outside our models.
If we never did that before maybe now would be a good time to start.  

Phil

> -----Original Message-----
> From: Russell Standish [mailto:r.standish at unsw.edu.au]
> Sent: Sunday, March 30, 2008 6:47 PM
> To: sy at synapse9.com; The Friday Morning Applied Complexity Coffee Group
> Subject: Re: [FRIAM] can you have 4 operating systems on one buss?
>
> On Sun, Mar 30, 2008 at 10:55:01AM -0400, Phil Henshaw wrote:
> >
> > The canonical example is of a resource that begins with having no
> limit for
> > a small community of users with various cooperative habits for
> exploiting
> > it.  If their habits constitute a growth system, the users will
> usually know
> > only their own individual experience and have no experiential
> information
> > about the approach of that limit.  It's not clear what their best
> source of
> > information would be about it, or how they would choose what to do at
> the
> > limits.
> >
> > What kind of information might indicate the approach of common
> resource
> > limits?  How would that be different from evidence that other users
> are
> > breaking their agreements?   As independent users of natural
> resources tend
> > to have less information about, or interest in, each other's
> particular
> > needs than, say, cyclists in a peloton, how would they begin to
> renegotiate
> > their common habits when circumstances require it?
> >
> > Phil
> >
>
> Interesting that you should have brought the tragedy of the commons
> into this. I recently read a paper by Juergen Kremer
> (http://www.rheinahrcampus.de/fileadmin/prof_seiten/kremer/MasterKeenEc
> onomics.PDF)
> discussing some work that Steve Keen and I have done on the theory of
> the firm. In it, he mentions that our framework can be applied to the
> tragedy of the commons case, and that under the same special
> conditions of prefectly rational competitors and frictionless
> response, a cooperative solution will emerge that exploits the commons
> without overloading it. The paper is in German, but the idea is pretty
> simple once you understand our theory of the firm stuff, which you can
> get from my website.
>
> Of course, real economic agents are neither rational, nor
> frictionless, and in our Complex Systems '04 paper, we explore just
> how much irrationality and how much friction is required to break the
> Keen ("monopoly") solution (corresponding to the benevolent dictator
> ToC
> solution) into the Cournot ("competitive") solution (corresponding to
> over exploitation of the ToC).
>
> Cheers
>
> --
>
> -----------------------------------------------------------------------
> -----
> A/Prof Russell Standish                  Phone [phone] (mobile)
> Mathematics
> UNSW SYDNEY 2052                 hpcoder at hpcoders.com.au
> Australia                                http://www.hpcoders.com.au
> -----------------------------------------------------------------------
> -----

[Marcus G. Daniels]

The reciprocal altruism of the peloton is interesting, but don't forget
the race finally turns to teams sacrificing their members, one by one,
for the sake of the final attack by the most capable rider...

[Steve Smith]

Marcus G. Daniels wrote:
> The reciprocal altruism of the peloton is interesting, but don't forget
> the race finally turns to teams sacrificing their members, one by one,
> for the sake of the final attack by the most capable rider...
>  
Good point.

And do the team's sacrifice their members or do the members sacrifice
themselves?

Is there a difference?

- Steve
PS. I don't follow any professional sports, including cycling... so I'm
sure I don't get many of the nuances!

[Marcus G. Daniels]

Steve Smith wrote:
> And do the team's sacrifice their members or do the members sacrifice
> themselves?
>
> Is there a difference?
>  
Yes, they even call them domestiques (servants).    Bicycle racing is a
corporate thing.

[Hugh Trenchard]

(Phil henshaw) "What kind of information might indicate the approach of
common resource limits? How would that be different from evidence that other
users are breaking their agreements? As independent users of natural
resources tend to have less information about, or interest in, each other's
particular needs than, say, cyclists in a peloton, how would they begin to
renegotiate their common habits when circumstances require it?"

Here is a short essay that looks at Phil's questions of resource consumption
from the perspective of a peloton analog.  It doesn't seek to answer the
questions, but rather proposes a model in which to analyze them.  It may be
rather simplistic against the backdrop of sophisticated economic theory, but
as a very real system, I suggest the dynamics of pelotons may provide
insight into them.  The scope of my essay may also be overly broad, and in
that respect, incomplete, but my hope is that there are a few kernels that
may assist Phil's analysis, or are at the very least, interesting.

Information exchange, resource consumption and sharing in bicycle pelotons:
a model for analyzing competitive systems

Hugh Trenchard

Bicycle racing is by definition competitive, and involves strategies for the
cooperative distribution and exploitation of individual and collective
resources. Individual resources exist in the form of energy available for
consumption within a rider's body, either in the form of glucose stored in
rider's livers and muscles, or body fats, and the physiological mechanisms
which allow riders to expend that energy. Rate of individual resource
consumption may be reduced by drafting, which occurs when riders are
positioned in zones of lower air pressure, either directly behind others
riders', or at angles to the wind direction. Riders in drafting positions
reduce energy expenditure by as much as 30 - 40% over a rider in front at
40km/hr, depending on positioning within the peloton (Hagberg and McCole,
1990).

Reduction of energy expenditure in drafting positions is also a collective,
or shared resource. It is a collective resource when riders in competitive
situations either cooperate or exploit this resource to maximally reduce
their own individual resource expenditure or the expenditure of allies.
Allies may be team-mates, but are also frequently competitors from different
teams who cooperate when a peloton has split into groups, thereby
temporarily becoming allies to achieve specific objectives, before again
becoming competitors. The relative and continuous balance between
cooperation and exploitation occurs most notably when a peloton has split
into groups of two or more, and the objective of group(s) ahead is to remain
ahead of following groups, while the reverse objective exists for groups
behind, which is to reintegrate groups ahead. In situations like these,
free-riders, quite literally, are prevalent, repleat with a number of modes
of punishment. A more detailed account of that, however, is beyond the scope
of this discussion.

In the course of their resource consumption, the information cyclists
receive or generate is largely visual. There is also vocal information, and,
at the highest levels there is nearly always communication exchanged between
riders within the peloton and sources outside the peloton (coaches or
"director sportifs"), via radio contact - an advancement in racing tactics
that has developed and been allowed in races for roughly 20 years now.
Generally riders have limited global information due to obstructed viewing
(i.e. blocked by riders surrounding them) and primarily receive only local
information about the riders immediately surrounding them. One reason
(albeit a secondary reason) for advancing or falling back within a peloton
is to gather information about the positions of competitors. Some of this
information may be relayed verbally through information links within the
peloton (other cyclists), or riders acquire the information by visual
observation, or through radio contact.

The information riders seek is primarily threefold:

1  competitor positioning

2  apparent rider resource consumption

3  course constraints



1. Competitor positioning

This is determined by


a.  local observation of riders in immediate 360 degree visual field, where
course topography is flat

b.  partial or complete global observations of peloton where elevation and
course configuration allow visual information to be obtained from higher or
lateral vantage points (e.g. if a cyclist is near the rear of a descending
peloton on an open road, the rider has a clear view of cyclists' positions
ahead);

c.  positional information may also be gleaned by implication, namely if a
cyclist is at the front, he or she knows all her competitors are behind, and
will see them if they try to pass. Similarly, but more anxiety causing, if a
cyclist is at the back, he will know all competitors are ahead of him.

2. Resource consumption

Information about resource consumption is evidenced by competitors' apparent
discomfort, such as facial contortions, body positions, or by other
indicators such as failures to take pulls at the front (during cooperative
situations), struggling to hold minimal distances between wheels,
deteriorating pedalling form, poor gear ratio selection, or observations
about fluid intake or food consumption during the race. For example, if a
rider has lost his water bottle at a critical point, others will have
exploitative information about his sugar levels.

3. Course constraints

This refers to the physical course and its changes: is there a hill
approaching, is there an obstacle approaching, is there a bend in the
course; how strong is the wind, and from what direction is it coming? In
road racing, courses may be out-and-back or point-to-point, and change
continuously and, aside from general course information obtained before
commencing the race, course predictability is relatively low; in road
circuit races, which may consist of several loops of a course of, say, 1 km
to 15km or more, the course repeats regularly and so there is a greater
degree of course predictability, in addition to information obtained before
hand; a track course is oval, is either 250m or 333m long and is banked, and
thus is highly regular and allows the greatest degree of predictability and
available global information.

All of these factors provide clues as to when individual and shared resource
limits are approaching. These limits arise primarily in the following
situations:


1.  Shared resources are lost, such as during sufficiently steep hill
climbs, when speeds fall to a point when drafting advantage is negligible
(<16km/h (Swain, 1990)) and differentials between cyclists'respective power
output capacities overwhelm the equalizing effects of any drafting
advantage;

2.  Shared resources are not-negotiated, such as during a final sprint for
the finish line, or other situations when speeds are beyond a certain
threshold between sets of rider causing peloton disintegration**

3.  Shared resources are too dangerous, such as on high-speed descents,
where collisions with others, obstacles or proceding on trajectories outside
physical course parameters (e.g. plummetting over a cliff on the outside of
a hairpin turn!) are avoided by maintaining distances outside of drafting
range).

Applying the peloton model

A peloton may thus be viewed as a basic resource sharing system which may
provide clues as to how resources are shared and consumed in other systems,
especially competitive ones - which arguably most such systems involving
resource consumption are. I suggest that, in principle, when we investigate
the question of how to re-negotiate resource sharing, we can first seek to
understand the nature of these categories of information: competitor
positioning, apparent resource consumption, and course constraints. These
factors by themselves are nothing new, but applying a peloton model to other
systems, at least in any rigourous fashion, is new.

When information about these factors is not available globally, as is most
often the case, we can examine features exhibited by other systems of
resource sharing that may be analogous to what occurs in pelotons. For
example, energy in a peloton is reduced, essentially, by following the paths
of other riders. Any natural system in which path following serves to reduce
energy expenditure is analogous to a peloton. As a simple example, when a
forager tramples a path through snow to a food source, that forager expends
more energy than all that follow in the established pathway. Forager
dynamics may be examined against the model of peloton dynamics and its
pattern thresholds.

In pelotons, thresholds exist where observable collective emergent
behaviours are exhibited, described by the following phases:

Phase 1 Transitional

As cyclists set off at the beginning of a race, there is a period during
which the speeds are sufficiently low for cyclists to have no physiological
necessity to draft one another, as they are all well below individual pain
thresholds or maximal power output capacity. The phase is characterized by
roughly random internal peloton movements, or low-pattern formation within
the peloton.

Phase II Rotational

As speeds increase, a transition occurs whereby resource sharing becomes
necessary as cyclists approach (but remain below) pain and maximal output
thresholds, and when the collective drafting resource is exploited. In this
phase, a balancing occurs between energy expenditure and optimal position
within the peloton. Because it is a competitive situation, it is better to
be positioned as close to the front as possible. As this is a continuous
imperative, rotational movements occur within the peloton, when riders move
up and down the peloton, or are caught in "eddies" whereby they advance for
relatively short distances within the peloton, before being shifted backward
again, and then attempt to move forward again. These movements occur while
riders attempt to use as little energy as possible to advance. So, where
there are riders who shift to the outside of the pack (facing the wind by
doing so), other riders will follow in their draft.
The result is a rotational pattern whereby riders advance up the sides for
relatively long stretches, while riders drop back within the peloton, and
while within
the peloton there are smaller-scale rotations, or eddies. The rotational
patterns which emerge are analogous to the roiling effects of boiling
liquid, as riders "heat up" by greater energy expenditure in moving forward,
and cool down by reduced energy expenditure in moving backward through the
peloton. Incidentally, this pattern is also similar to rotational patterns
observed in emperor penguin huddles (Ancel, et al., 1997; Stead, 2003).


Phase III Stretching

A third phase transition occurs when the pace shifts up beyond another
threshold, whereby the speeds are too high for there to be continuous
rotational movement within the peloton, and the peloton stretches into a
single line. This phase, while easily observable, is a precurser to a final
transition where the peloton begins to splinter: individual riders fall off
the back, or separations occur in the line of riders which following riders
cannot bridge, resulting in regions of peloton instability and loss of
cohesion.


Phase IV Disintegration

In this last phase riders fall outside of drafting range, and cooperation
(or coupling between cyclists) disintegrates as cyclists become either in
direct competition with the each other. This phase is analogous to the phase
change between liquid and gas, as cyclists move outside of drafting range,
thereby de-coupling. In bicycle racing this phase is usually temporary,
however, as speeds drop quickly, and, through a series of agglomerations,
the entire peloton either reintegrates or sub-groups form which cooperate
internally but which are also in direct conflict with each other. In the
case of sub-groups in conflict, it is the objective of chasing groups to
reintegrate groups ahead, while it is the objective of groups ahead to stay
ahead of chasing groups.

Conclusion

Although a peloton is a resource sharing system consisting of human agents
with competitive human objectives, it is also an energetically dynamic
system that exhibits self-organized thresholds and emergent patterns.  It is
reasonable to speculate that when we look at other natural systems in which
resources are shared and exploited, there are analogous patterns which
emerge at certain energy consumption thresholds. The physical manifestations
of such thresholds and emergent patterns may not be easy to identify, but
here we have a microcosmic model of a competitive, self-organizing system
which may provide some clues.

____________________________

References


Hagberg, J., McCole, S. The Effect of Drafting and Aerodynamic Equipment on
Energy Expenditure During Cycling, 1990, Cycling Science, 2, p. 20

Swain, D. Cycling Uphill and Downhill. Sportscience 2(4),
sportsci.org/jour/9804/dps.html, 1998 (2682 words)

**which threshold I have previously argued on the basis of a coupling model,
having called it the peloton convergence ratio (PCR). PCR =(Wa-Wb/Wa)/D
where Wa is the maximum power output (watts) of cyclist A at any given
moment; Wb is the maximum power output of cyclist B at that moment (assuming
Wa>Wb), and D is the percent energy savings due to drafting at the velocity
travelled: Trenchard, H., Mayer-Kress, G. Self-Organized Oscillator Coupling
and Synchronization in Bicycle Pelotons During Mass-start bicycle racing.
Book of Abstracts, International Conference on Control and Synchronization
of Dynamical Systems, Oct 4-7, 2005, Leon, Gto, Mexico. Ratios of =<1 and
cyclists remain coupled; >1 and cyclists de-couple, when points of
instability in pelotons occur and peloton disintegration begins.

Ancel, A., Visser, H., Handrick, Y., Masman, D., Le Maho, Y. Energy Saving
in huddling penguins. Nature, Vol. 385. 23 Jan 1997; Stead, G. An Artificial
Life Simulation to Investigate the Huddling Behaviour of Emperor Penguins.
Submitted in partial fulfillment for the degree of MSc in software systems
technology.

[Phil Henshaw-2]

Hugh,

>
> (Phil henshaw) "What kind of information might indicate the approach of
> common resource limits? How would that be different from evidence that
> other
> users are breaking their agreements? As independent users of natural
> resources tend to have less information about, or interest in, each
> other's
> particular needs than, say, cyclists in a peloton, how would they begin
> to
> renegotiate their common habits when circumstances require it?"

[ph] Great, you apparently see the general problem.  The form of the
information you're looking for needs to be rediscovered in every situation.
It's flying blind.   If you're not looking for the uncharacteristic
indications of how you're interacting with other independent actors in your
environment you'll miss a whole lot more than if you do look for it.  

The most frequent long range forecaster of the approach of common resource
limits is diminishing returns, since resource exploitation is done by taking
easy things first. It invariably begins by discovering more and bigger easy
things and ends in discovering fewer and smaller ones later.  If there are
multiple users of a resource they'll skillfully avoid conflict with each
other until they're abruptly forced into conflict when the options to avoid
it dwindle to zero in the circumstance (say two species needing to turn to
their less favorite food and colliding).  That end game is first observable
as an eruption of complexity in the dodges needed by each user to stay out
of another user's way, and then by things like cheating on the conventions
for staying out of each others way that developed doing that...   The growth
curves of diminishing returns and complexity in the environment are strong
signals telegraphing the state of relationships among the whole community of
otherwise 'unseen' and 'unrecognized' users that seek to avoid conflict with
each other.

In terms of a peloton my first thought is much like yours.   I'd guess that
most competitors who plan on breaking with the pack will wait for a good
time to do that.  At that time in the race they'll closely watch each
other's hesitations and glances to read the advantageous time to break the
temporary 'agreement' to share the load...   As a racer I'd be looking at
all the things on your list, sort of integrated as a total measure of the
'alacrity' of my peloton mates in mounting each rise.  It's at the point
where the 'spring in their step' starts to fall off that I'd look for a
chance to make my move, timed so the competitor I'm worried about is in a
disadvantageous position, something like that.  

In that case the 'resource depletion signal' is the switch from homeostatic
stability in the pace to the phase of positive feedback in the group's
weakening stride, the first appearance of huffing and puffing you might say.
That's the indication of phase 4 in the basic 5 phase developmental sequence
in any process from its beginning to end, 1??.2????3??4?`?5.??  The
information about when the peloton is no longer brightly responding to a
increase in grade is available to every rider about equally, but not
perceived the same way by each.   Each one will also have different ways of
conceiving their separate strategies for when the safety of the group
breaks.   In the environmental case of growing needs for both food and fuel
and farmers competing for aerable land forced to decide whose food gets
squeezed out by whose fuels, the comeraterie of the end game may be missing
of course...

Phil

>
> Here is a short essay that looks at Phil's questions of resource
> consumption
> from the perspective of a peloton analog.  It doesn't seek to answer
> the
> questions, but rather proposes a model in which to analyze them.  It
> may be
> rather simplistic against the backdrop of sophisticated economic
> theory, but
> as a very real system, I suggest the dynamics of pelotons may provide
> insight into them.  The scope of my essay may also be overly broad, and
> in
> that respect, incomplete, but my hope is that there are a few kernels
> that
> may assist Phil's analysis, or are at the very least, interesting.
>
> Information exchange, resource consumption and sharing in bicycle
> pelotons:
> a model for analyzing competitive systems
>
> Hugh Trenchard
>
> Bicycle racing is by definition competitive, and involves strategies
> for the
> cooperative distribution and exploitation of individual and collective
> resources. Individual resources exist in the form of energy available
> for
> consumption within a rider's body, either in the form of glucose stored
> in
> rider's livers and muscles, or body fats, and the physiological
> mechanisms
> which allow riders to expend that energy. Rate of individual resource
> consumption may be reduced by drafting, which occurs when riders are
> positioned in zones of lower air pressure, either directly behind
> others
> riders', or at angles to the wind direction. Riders in drafting
> positions
> reduce energy expenditure by as much as 30 - 40% over a rider in front
> at
> 40km/hr, depending on positioning within the peloton (Hagberg and
> McCole,
> 1990).
>
> Reduction of energy expenditure in drafting positions is also a
> collective,
> or shared resource. It is a collective resource when riders in
> competitive
> situations either cooperate or exploit this resource to maximally
> reduce
> their own individual resource expenditure or the expenditure of allies.
> Allies may be team-mates, but are also frequently competitors from
> different
> teams who cooperate when a peloton has split into groups, thereby
> temporarily becoming allies to achieve specific objectives, before
> again
> becoming competitors. The relative and continuous balance between
> cooperation and exploitation occurs most notably when a peloton has
> split
> into groups of two or more, and the objective of group(s) ahead is to
> remain
> ahead of following groups, while the reverse objective exists for
> groups
> behind, which is to reintegrate groups ahead. In situations like these,
> free-riders, quite literally, are prevalent, repleat with a number of
> modes
> of punishment. A more detailed account of that, however, is beyond the
> scope
> of this discussion.
>
> In the course of their resource consumption, the information cyclists
> receive or generate is largely visual. There is also vocal information,
> and,
> at the highest levels there is nearly always communication exchanged
> between
> riders within the peloton and sources outside the peloton (coaches or
> "director sportifs"), via radio contact - an advancement in racing
> tactics
> that has developed and been allowed in races for roughly 20 years now.
> Generally riders have limited global information due to obstructed
> viewing
> (i.e. blocked by riders surrounding them) and primarily receive only
> local
> information about the riders immediately surrounding them. One reason
> (albeit a secondary reason) for advancing or falling back within a
> peloton
> is to gather information about the positions of competitors. Some of
> this
> information may be relayed verbally through information links within
> the
> peloton (other cyclists), or riders acquire the information by visual
> observation, or through radio contact.
>
> The information riders seek is primarily threefold:
>
> 1  competitor positioning
>
> 2  apparent rider resource consumption
>
> 3  course constraints
>
>
>
> 1. Competitor positioning
>
> This is determined by
>
>
> a.  local observation of riders in immediate 360 degree visual field,
> where
> course topography is flat
>
> b.  partial or complete global observations of peloton where elevation
> and
> course configuration allow visual information to be obtained from
> higher or
> lateral vantage points (e.g. if a cyclist is near the rear of a
> descending
> peloton on an open road, the rider has a clear view of cyclists'
> positions
> ahead);
>
> c.  positional information may also be gleaned by implication, namely
> if a
> cyclist is at the front, he or she knows all her competitors are
> behind, and
> will see them if they try to pass. Similarly, but more anxiety causing,
> if a
> cyclist is at the back, he will know all competitors are ahead of him.
>
> 2. Resource consumption
>
> Information about resource consumption is evidenced by competitors'
> apparent
> discomfort, such as facial contortions, body positions, or by other
> indicators such as failures to take pulls at the front (during
> cooperative
> situations), struggling to hold minimal distances between wheels,
> deteriorating pedalling form, poor gear ratio selection, or
> observations
> about fluid intake or food consumption during the race. For example, if
> a
> rider has lost his water bottle at a critical point, others will have
> exploitative information about his sugar levels.
>
> 3. Course constraints
>
> This refers to the physical course and its changes: is there a hill
> approaching, is there an obstacle approaching, is there a bend in the
> course; how strong is the wind, and from what direction is it coming?
> In
> road racing, courses may be out-and-back or point-to-point, and change
> continuously and, aside from general course information obtained before
> commencing the race, course predictability is relatively low; in road
> circuit races, which may consist of several loops of a course of, say,
> 1 km
> to 15km or more, the course repeats regularly and so there is a greater
> degree of course predictability, in addition to information obtained
> before
> hand; a track course is oval, is either 250m or 333m long and is
> banked, and
> thus is highly regular and allows the greatest degree of predictability
> and
> available global information.
>
> All of these factors provide clues as to when individual and shared
> resource
> limits are approaching. These limits arise primarily in the following
> situations:
>
>
> 1.  Shared resources are lost, such as during sufficiently steep hill
> climbs, when speeds fall to a point when drafting advantage is
> negligible
> (<16km/h (Swain, 1990)) and differentials between cyclists'respective
> power
> output capacities overwhelm the equalizing effects of any drafting
> advantage;
>
> 2.  Shared resources are not-negotiated, such as during a final sprint
> for
> the finish line, or other situations when speeds are beyond a certain
> threshold between sets of rider causing peloton disintegration**
>
> 3.  Shared resources are too dangerous, such as on high-speed descents,
> where collisions with others, obstacles or proceding on trajectories
> outside
> physical course parameters (e.g. plummetting over a cliff on the
> outside of
> a hairpin turn!) are avoided by maintaining distances outside of
> drafting
> range).
>
> Applying the peloton model
>
> A peloton may thus be viewed as a basic resource sharing system which
> may
> provide clues as to how resources are shared and consumed in other
> systems,
> especially competitive ones - which arguably most such systems
> involving
> resource consumption are. I suggest that, in principle, when we
> investigate
> the question of how to re-negotiate resource sharing, we can first seek
> to
> understand the nature of these categories of information: competitor
> positioning, apparent resource consumption, and course constraints.
> These
> factors by themselves are nothing new, but applying a peloton model to
> other
> systems, at least in any rigourous fashion, is new.
>
> When information about these factors is not available globally, as is
> most
> often the case, we can examine features exhibited by other systems of
> resource sharing that may be analogous to what occurs in pelotons. For
> example, energy in a peloton is reduced, essentially, by following the
> paths
> of other riders. Any natural system in which path following serves to
> reduce
> energy expenditure is analogous to a peloton. As a simple example, when
> a
> forager tramples a path through snow to a food source, that forager
> expends
> more energy than all that follow in the established pathway. Forager
> dynamics may be examined against the model of peloton dynamics and its
> pattern thresholds.
>
> In pelotons, thresholds exist where observable collective emergent
> behaviours are exhibited, described by the following phases:
>
> Phase 1 Transitional
>
> As cyclists set off at the beginning of a race, there is a period
> during
> which the speeds are sufficiently low for cyclists to have no
> physiological
> necessity to draft one another, as they are all well below individual
> pain
> thresholds or maximal power output capacity. The phase is characterized
> by
> roughly random internal peloton movements, or low-pattern formation
> within
> the peloton.
>
> Phase II Rotational
>
> As speeds increase, a transition occurs whereby resource sharing
> becomes
> necessary as cyclists approach (but remain below) pain and maximal
> output
> thresholds, and when the collective drafting resource is exploited. In
> this
> phase, a balancing occurs between energy expenditure and optimal
> position
> within the peloton. Because it is a competitive situation, it is better
> to
> be positioned as close to the front as possible. As this is a
> continuous
> imperative, rotational movements occur within the peloton, when riders
> move
> up and down the peloton, or are caught in "eddies" whereby they advance
> for
> relatively short distances within the peloton, before being shifted
> backward
> again, and then attempt to move forward again. These movements occur
> while
> riders attempt to use as little energy as possible to advance. So,
> where
> there are riders who shift to the outside of the pack (facing the wind
> by
> doing so), other riders will follow in their draft.
> The result is a rotational pattern whereby riders advance up the sides
> for
> relatively long stretches, while riders drop back within the peloton,
> and
> while within
> the peloton there are smaller-scale rotations, or eddies. The
> rotational
> patterns which emerge are analogous to the roiling effects of boiling
> liquid, as riders "heat up" by greater energy expenditure in moving
> forward,
> and cool down by reduced energy expenditure in moving backward through
> the
> peloton. Incidentally, this pattern is also similar to rotational
> patterns
> observed in emperor penguin huddles (Ancel, et al., 1997; Stead, 2003).
>
>
> Phase III Stretching
>
> A third phase transition occurs when the pace shifts up beyond another
> threshold, whereby the speeds are too high for there to be continuous
> rotational movement within the peloton, and the peloton stretches into
> a
> single line. This phase, while easily observable, is a precurser to a
> final
> transition where the peloton begins to splinter: individual riders fall
> off
> the back, or separations occur in the line of riders which following
> riders
> cannot bridge, resulting in regions of peloton instability and loss of
> cohesion.
>
>
> Phase IV Disintegration
>
> In this last phase riders fall outside of drafting range, and
> cooperation
> (or coupling between cyclists) disintegrates as cyclists become either
> in
> direct competition with the each other. This phase is analogous to the
> phase
> change between liquid and gas, as cyclists move outside of drafting
> range,
> thereby de-coupling. In bicycle racing this phase is usually temporary,
> however, as speeds drop quickly, and, through a series of
> agglomerations,
> the entire peloton either reintegrates or sub-groups form which
> cooperate
> internally but which are also in direct conflict with each other. In
> the
> case of sub-groups in conflict, it is the objective of chasing groups
> to
> reintegrate groups ahead, while it is the objective of groups ahead to
> stay
> ahead of chasing groups.
>
> Conclusion
>
> Although a peloton is a resource sharing system consisting of human
> agents
> with competitive human objectives, it is also an energetically dynamic
> system that exhibits self-organized thresholds and emergent patterns.
> It is
> reasonable to speculate that when we look at other natural systems in
> which
> resources are shared and exploited, there are analogous patterns which
> emerge at certain energy consumption thresholds. The physical
> manifestations
> of such thresholds and emergent patterns may not be easy to identify,
> but
> here we have a microcosmic model of a competitive, self-organizing
> system
> which may provide some clues.
>
> ____________________________
>
> References
>
>
> Hagberg, J., McCole, S. The Effect of Drafting and Aerodynamic
> Equipment on
> Energy Expenditure During Cycling, 1990, Cycling Science, 2, p. 20
>
> Swain, D. Cycling Uphill and Downhill. Sportscience 2(4),
> sportsci.org/jour/9804/dps.html, 1998 (2682 words)
>
> **which threshold I have previously argued on the basis of a coupling
> model,
> having called it the peloton convergence ratio (PCR). PCR =(Wa-Wb/Wa)/D
> where Wa is the maximum power output (watts) of cyclist A at any given
> moment; Wb is the maximum power output of cyclist B at that moment
> (assuming
> Wa>Wb), and D is the percent energy savings due to drafting at the
> velocity
> travelled: Trenchard, H., Mayer-Kress, G. Self-Organized Oscillator
> Coupling
> and Synchronization in Bicycle Pelotons During Mass-start bicycle
> racing.
> Book of Abstracts, International Conference on Control and
> Synchronization
> of Dynamical Systems, Oct 4-7, 2005, Leon, Gto, Mexico. Ratios of =<1
> and
> cyclists remain coupled; >1 and cyclists de-couple, when points of
> instability in pelotons occur and peloton disintegration begins.
>
> Ancel, A., Visser, H., Handrick, Y., Masman, D., Le Maho, Y. Energy
> Saving
> in huddling penguins. Nature, Vol. 385. 23 Jan 1997; Stead, G. An
> Artificial
> Life Simulation to Investigate the Huddling Behaviour of Emperor
> Penguins.
> Submitted in partial fulfillment for the degree of MSc in software
> systems
> technology.
>
>