On Emergence and Decision Making in Complex Systems

[Sudhira H S-2]

Hi,

I was wondering if we were to make decisions in complex systems, how
one can distinguish outcomes of decision-making with emergence. When
modelling complex systems, the emergent phenomenon of the system can
be captured through different scenarios. But if one were forced to
make decisions on a complex system, how is that the emergence and
outcomes of decision-making be looked at?

I think the emergent phenomenon can be one of the realisation of a
decision. Suppose in the case of multi-objective / multi-stakeholder
environment, I try and capture the behaviours of different groups. How
is that one distinguish emergence with the outcomes of choice
(decisions) exercised by different stakeholders? I would request any
pointers / literature on the same.

Kind Regards,

Sudhira H. S.
--
----------------------------------------------------------------------------------------------------------------
Research Student, Ph.D.,
Centre for Sustainable Technologies and Department of Management Studies,
Indian Institute of Science,
Bangalore - 560 012, Karnataka State, INDIA
Email: sudhira at mgmt.iisc.ernet.in, hs.sudhira at gmail.com
----------------------------------------------------------------------------------------------------------------

[Stephen Guerin]

Hello Sudhira,

> I was wondering if we were to make decisions in complex
> systems, how one can distinguish outcomes of decision-making
> with emergence. When modelling complex systems, the emergent
> phenomenon of the system can be captured through different
> scenarios. But if one were forced to make decisions on a
> complex system, how is that the emergence and outcomes of
> decision-making be looked at?

I know I'm not grasping the full meaning of your question but here is a shot
at a response:

A distributed system of decision-makers can exhibit emergent properties. eg.
flocking behavior from boids making a decision where to move next. Flocking,
like all examples of emergence I've encountered, involves spontaneous
symmetry breaking (I'd be interested if someone has a counter example).

So assuming symmetry breaking is a necessary condition of emergence, you
could start to distinguish emergent outcomes by looking at their symmetries.



> How is that one distinguish emergence with the outcomes of choice
> (decisions) exercised by different stakeholders?

Using the flocking example again, I think of the outcome of the stakeholders
(boids) to be their next position in time. The emergent outcome, however, is
the flocking behavior (symmetry break in linear momentum of the population).

I hope that helps more than it confuses :-)

-Steve

________________________________________
Stephen.Guerin at Redfish.com
www.Redfish.com
624 Agua Fria Street, Santa Fe, NM 87501
mobile: [phone]
office: Santa Fe, NM [phone] / London, UK [phone]

> -----Original Message-----
> From: Sudhira H S [mailto:hs.sudhira at gmail.com]
> Sent: Friday, May 12, 2006 12:17 AM
> To: The Friday Morning Applied Complexity Friam;
> CAS-Group at yahoogroups.com
> Subject: [FRIAM] On Emergence and Decision Making in Complex Systems
>
> Hi,
>
> I was wondering if we were to make decisions in complex
> systems, how one can distinguish outcomes of decision-making
> with emergence. When modelling complex systems, the emergent
> phenomenon of the system can be captured through different
> scenarios. But if one were forced to make decisions on a
> complex system, how is that the emergence and outcomes of
> decision-making be looked at?
>
> I think the emergent phenomenon can be one of the realisation
> of a decision. Suppose in the case of multi-objective /
> multi-stakeholder environment, I try and capture the
> behaviours of different groups. How is that one distinguish
> emergence with the outcomes of choice
> (decisions) exercised by different stakeholders? I would
> request any pointers / literature on the same.
>
> Kind Regards,
>
> Sudhira H. S.
> --
> --------------------------------------------------------------
> --------------------------------------------------
> Research Student, Ph.D.,
> Centre for Sustainable Technologies and Department of
> Management Studies, Indian Institute of Science, Bangalore -
> 560 012, Karnataka State, INDIA
> Email: sudhira at mgmt.iisc.ernet.in, hs.sudhira at gmail.com
> --------------------------------------------------------------
> --------------------------------------------------
>
> ============================================================
> 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
>
>

[Jochen Fromm-3]

I guess what you are interested in the management aspect:
what do you do as a manager if you are faced with a complex system
in a concrete real-world situation, and how do you find the
right decision to manage a complex system.  You might be
interested in Dietrich Doerner's book "The Logic of Failure -
Recognizing and Avoiding Error in Complex Situations".
Doerner is a Germany psychology professor, and his
recommendations for the right decisions are simple.
We should be aware that our cognitive models are wrong and our
thinking shortsighted: "An individual's reality model can be right
or wrong, complete or incomplete. As a rule it will be both incomplete
and wrong, and one would do well to keep that probability in mind."

Doerner further argues that there is no standard solution, silver
bullet or one-size-fits-all solution in many comlex situtations,
because every complex situation is different (complexity has many
varieties, but simplicity has a unified form). Our ordinary common
sense is probably the best tool we have to solve complex problems.

Finally he recommends the use of simulations and suitable models
in order to deal with complex systems. This is especially recommendable
for systems with a high probability of emergent properties. It is of
course important to find the right level of detail, too little details
means oversimplification, too much details means the model is too
complex and one easily drowns in data.

The answer of Stephen is interesting. Do all examples of
emergence involve some form of spontaneous symmetry breaking ?
If you think of emergence as a process of pattern formation,
then the new pattern obviously breaks the symmetry that existed
before the pattern appeared. Yet often for every symmetry that
is broken a new symmetry seems to appear.

The classical examples for swarm formation and swarm
intelligence are flocking and (ant) foraging, respectively.
Further popular examples are pile building termites
(if you find a chip then pick it up unless you're already
carrying a chip in which case drop it), Langton's ant
and Schelling's segregation model.

Can you find a symmetry breaking in all these examples ?
Probably yes, but one can find often both, a symmetry
breaking and a symmetry making at the same time.
A shoal of fish for example may show more or less
translational symmetry before the creation of the flock
(in the disordered state), and rotational symmetry afterwards
(in the ordered state, for instance in a spherical flock).
The same argument applies to pile building termites:
first the translational symmetry seems to be broken,
and then a new local rotational symmetry appears in
for of spherical heaps, see
http://ccl.northwestern.edu/netlogo/models/Termites

-J.

[Sudhira H S-2]

Thanks Stephen and Jochen for the quick responses. I think Jochen got
my question right!
I have checked the Flocking and Termites model. By way of looking for
emergence, are we restricting only to symmetry breaking and pattern
formations? Isn't emergence about a continuum of both for any given
complex system?

All right, I understand that we have limited cognitive abilities. In
fact we are not wired for that. Robin M. Hogarth has done some similar
work in the sense that there are about 30 judgemental errors and
biases we normally make. You may be interested in his work:
http://www.amazon.com/gp/product/0471914797/002-2052677-8240030?v=glance&n=283155
(I haven't read the book, though I know his work is very relevant).
Judgemental errors and biases also extend the idea of bounded
rationality.

There are two key points you state while discussing on Dietrich
Doerner's book: One is that our modelling capabilities are limited.
And this is never complete. Yes of course. And hence one has to also
rely on "common sense". The second fact that Simulations can really
help. Of course, simulations has come in handy for generating
different scenarios / outcomes of a same system. Here we would still
forcing in our biases based on the mental models we construct for the
problem. Yet, ABM allows us to reasonably emulate some of these
systems.

Somewhere down the line, my problem was how in
multi-objective/multiple stakeholder situations, management decisions
can be taken from a planning and decision-making perspective at an
operational level towards achieving an "expected" outcome. When
systems are complex enough, the emergent phenomenon need not be the
"expected" outcome.

I shall look into the papers you sent and then get back.

Thanks and Regards,
Sudhira

On 5/12/06, Jochen Fromm <fromm at vs.uni-kassel.de> wrote:

>
> I guess what you are interested in the management aspect:
> what do you do as a manager if you are faced with a complex system
> in a concrete real-world situation, and how do you find the
> right decision to manage a complex system.  You might be
> interested in Dietrich Doerner's book "The Logic of Failure -
> Recognizing and Avoiding Error in Complex Situations".
> Doerner is a Germany psychology professor, and his
> recommendations for the right decisions are simple.
> We should be aware that our cognitive models are wrong and our
> thinking shortsighted: "An individual's reality model can be right
> or wrong, complete or incomplete. As a rule it will be both incomplete
> and wrong, and one would do well to keep that probability in mind."
>
> Doerner further argues that there is no standard solution, silver
> bullet or one-size-fits-all solution in many comlex situtations,
> because every complex situation is different (complexity has many
> varieties, but simplicity has a unified form). Our ordinary common
> sense is probably the best tool we have to solve complex problems.
>
> Finally he recommends the use of simulations and suitable models
> in order to deal with complex systems. This is especially recommendable
> for systems with a high probability of emergent properties. It is of
> course important to find the right level of detail, too little details
> means oversimplification, too much details means the model is too
> complex and one easily drowns in data.
>
> The answer of Stephen is interesting. Do all examples of
> emergence involve some form of spontaneous symmetry breaking ?
> If you think of emergence as a process of pattern formation,
> then the new pattern obviously breaks the symmetry that existed
> before the pattern appeared. Yet often for every symmetry that
> is broken a new symmetry seems to appear.
>
> The classical examples for swarm formation and swarm
> intelligence are flocking and (ant) foraging, respectively.
> Further popular examples are pile building termites
> (if you find a chip then pick it up unless you're already
> carrying a chip in which case drop it), Langton's ant
> and Schelling's segregation model.
>
> Can you find a symmetry breaking in all these examples ?
> Probably yes, but one can find often both, a symmetry
> breaking and a symmetry making at the same time.
> A shoal of fish for example may show more or less
> translational symmetry before the creation of the flock
> (in the disordered state), and rotational symmetry afterwards
> (in the ordered state, for instance in a spherical flock).
> The same argument applies to pile building termites:
> first the translational symmetry seems to be broken,
> and then a new local rotational symmetry appears in
> for of spherical heaps, see
> http://ccl.northwestern.edu/netlogo/models/Termites
>
> -J.
>
>
> ============================================================
> 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