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8/9/2019 Presentation from May 10, 2005 Dinner Meeting
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Systems and Software Consortium | 2214 Rock Hill Road, Herndon, VA 20170-4227
Phone: (703)742-8877 | FAX: (703)742-7200
www.systemsandsoftware.org
Practical Applications
of Complexity Theory
May 10, 2005
Sarah Sheard
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An expanded presentation of the symposium paper
Practical Applications of Complexity Theory
for Systems Engineers
To be given by at INCOSE
July 12, 2005, 4:30 pm
Rochester, NY
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Topics
System development paradoxes Chaos theory
Complexity theory
Complex adaptive systems
Suggestions for systems engineers
References
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Paradoxes with system development
Everyone wants system enterprise architecting, but no onereally follows through on it. The drawings hardly end up
driving anything.
Any really big systems needing to be designed are obsolete
by the time they get funded (even complicated analyses are
obsolete by the time they are complete). We try to stabilize requirements so we can build something,
but requirements creep remains the number one problem, and
its usually the customer who makes the changes.
We are building systems of systems, but no one lets out
contracts for systems of systems, they let out contracts forsystems or elements of systems. They fund, and produce
requirements for, only the pieces.
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Paradoxes with system development
Revenge effects:...the very steps we take to solve a problemcome back and bite us. For example, those who clean their
kitchens the most end up having the most antiseptic-resistant
bacteria. (Reference: Tenner)
Cause and effect become complicated...you find a problem
and look for its cause...then analyze it, and it has manycauses...find the reasons for them, and pretty soon you have
to solve everything in the world.
Any change you try to make engenders resistance that tries to
undo all your good work, and often successfully (e.g.,
technology insertion). You set up an assessment method to check how well some-
one does something in general, but pretty soon everyone
starts preparing for the test, and only the test.
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Paradoxes
Can these paradoxes be resolved by lookingthrough a different view, that of complexity?
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Chaos theory: Precursor to Complexity
Order exists within apparent randomness, e.g. drips of a faucet, wildlife
population
Simple systems can cause complex behavior
all they need is nonlinearity
Small nonlinearity factor in wildlife
population equation leads to steady state
Larger nonlinearity leads to boom/bust
oscillation
As nonlinear factor increases, cycle
doubles again until becoming chaotic
This is reproduced in many experimental
and mathematical domains[e.g., x(next) = a x (1-x) ]
Nonlinearity factor
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Chaos Theory conclusions
Simple equations do notimply
simple behavior
Strange attractors and fractals
describe nature better than linear
equations
Starting close together does not
imply ending close together...butterfly effect
End points diverge from nearly
indistinguishable starting points
The universe does not work
mostly like a predictable,controllable machine
Yet we need to predict and control
our projects and programs
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Complexity Theory
Chaos Theory
describes one
dimension
What happens at
the transition fromorder to chaos?
Many systems
adapt to live at the
edge of chaos!
Goals:
Source: http://www.theory.org/fracdyn/
neurodyn/langton-bifurcation.html
Characterize complex adaptive systems
Look at what we engineer in terms of complex adaptive systems
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Edge of Chaos
Order :Too littlecommunication
Chaos:Too unstable
Complex Adaptive systemsadapt toward the Edge of Chaos
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Critical point between Chaos and Order
Power law of events at the critical point When a sand pile is at critical angle, [number of grains falling
when one is added] follows a power law
So does number of earthquakes, etc.
Catastrophes are part of critical state
Source: http://www.theory.org/fracdyn/
neurodyn/langton-bifurcation.html
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Complexity Theory
Complexity theory is based on relationships, emergence,patterns and iterations
Complexity theory maintains that the universe is full of
systems (such as weather systems, immune systems,
and social systems) that are complex and constantly
adapting to their environment*
Complexity Theory examines the implications of such
interacting systems
*Peter Fryer, http://www.trojanmice.com/articles/complexadaptivesystems.htm
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Complex Adaptive Systems
1. Order is emergent, not predetermined (flock not building)2. Systems history is irreversible
3. Systems future is often unpredictable
Self-organizing
Includes agents: semi-autonomous building blocks following rules,seeking to optimize something by evolving over time (e.g. flora and
fauna in an ecosystem)
Fitness of the agent evolves in a complex manner (fitness
landscape is complex)
System as a whole (e.g. ecosystem) becomes more fit as itbecomes more complex (more connected, more intelligent)
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Scale of Systems
Ordinary Systems*(can be satisfactorily
treated as autonomous)
Systems of Systems*
(have a system integrator)
Complex Systems*
(adaptive, homeostatic)
*Taxonomy and terms by Michael L. Kuras and Brian E. White of Mitre Corp.
Ball BearingsOne Software Subroutine
MREs and Bullets
...
LSI Chip
Hoover Dam
Boeing 747
Space Shuttle
Windows Operating
System
...
Air Traffic Control
Ballistic Missile Defense
Homeland Security
Human Civilization
Less Complex,
Deterministic
More Complex,
Stochastic
MRE = Meals ready to eat.
LSI = large-scale integration
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Complex adaptive systems today
The world of systems is far more like biological complexadaptive systems than like clockwork mechanical
systems. Think of the larger system your system fits into
as biological, with a homeostatic mechanism...resisting
your changes... e.g. government and bureaucracies.
You are always only changing out pieces of ongoingliving systems, never actually creating a new system.
Hence the design (enterprise architecture) is always
ongoing, at best describing a living, changing reality,
never a true predictive plan. Your system changes its environment just by existing.
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Implications for paradoxes (1)
Think of the larger system you fit into as a biological, with homeostatic
mechanism...resisting your changes... e.g. government, bureaucracies
Any change you try to make engenders resistance that tries to
undo all your good work, and often successfully (e.g.,
technology insertion). Note homeostasis, and plan for it.
Cause and effect become complicated...you find a problem andlook for its cause...then analyze it and it has many causes...find
the reasons for them, and pretty soon you have to solve
everything in the world. Understand that cause and effect are
first-order, mechanistic, linear concepts that dont make so
much sense in complex systems. Try instead to understand
causal loops and system feedback.
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Implications for paradoxes (2)
You are always only changing out pieces of ongoing living systems,
never actually creating a new system, hence enterprise architecture isalways ongoing, at best describing a living, changing reality, never a true
predictive plan
We are building systems of systems, but no one lets out contracts
for systems of systems, they let out contracts for systems or
elements of systems. They fund, and produce requirements for,only the pieces.
Everyone wants system enterprise architecting, but no one really
follows through on it. The drawings hardly end up driving
anything.
Consider these as simple facts. The architecture of a system-of-systems is just the as-is description of an organism at one time.
The system will adapt on its own, not according to someones plan.
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Implications for paradoxes (3)
Your system changes its environment just by existing.
Any really big systems needing to be designed are obsolete
by the time they get funded (even complicated analyses are
obsolete by the time they are complete)
Consider different kinds of analyses and design, such as
genetic algorithm analyses, real options valuation, and set-
based design approaches. See references by McConnell,
Shisko, and Kennedy.
McConnell: Emergence: Applying the Principles using Genetic
Algorithms to derive [production deployment] schedules: A
near-optimal solution was found within minutes as against days.
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Implications for paradoxes (4)
Your system changes its environment just by existing. We try to stabilize requirements so we can build something,
but requirements creep remains the number one problem,
and its usually the customer who makes the changes.
Revenge effects:...the very steps we take to solve a problem
come back and bite us. For example, those who clean theirkitchens the most end up having the most antiseptic-resistant
bacteria.
You set up an assessment method to check how well some-
one does something in general, but pretty soon everyone
starts preparing for the test, and only the test.Start thinking of systems as complex adaptive systems. See
suggestions in symposium paper.
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Suggestions for Systems Engineers
Understand the problemspace better Ask more questions
Understand the
environment
Make better mental models
Make specific
improvements in: Modeling and simulation
Design
Risk identification and
management
Change management
Help management Embrace change Predict trends
Change program
management
Reconsider the distribution
of enterprise control
Focus research Look for data on
experientially derived
heuristics
Evolve SE principles basedon complexity theory
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So Where Are We Now?
The significant problems we have cannot be solved atthe same level of thinking with which we created them
- Albert Einstein
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References and Recommended Reading
Fryer, Peter. What are Complex Adaptive Systems? htttp://www.trojanmice.com/articles/
complexadaptivesystems.htm .Gleick, James. Chaos: The Making of a New Science. New York: Viking, 1987.
Kennedy, Michael N. Product Development in the Lean Enterprise: Why Toyotas System is FourTimes More Productive and How You Can Implement It. Richmond, Virginia: The Oaklea Press,2003.
Kuras, M.L. and Brian E. White,Engineering Enterprises using Complex Systems Engineering, Mitre
report MP 05B 0000003, 2005
Langtons Complexity at http://www.theory.org/fracdyn/neurodyn/langton-bifurcation.html.
Lewin, Roger. Complexity: Life at the Edge of Chaos. New York: Collier Books, 1992.
McConnell, George R. Emergence: Applying the Principles using Genetic Algorithms to deriveSchedules. Proceedings of INCOSE. Las Vegas, Nevada, 2003.
Sanders, T. Irene. Strategic Thinking and the New Science: Planning in the Midst of Chaos,Complexity, and Change. New York: The Free Press, 1998.
Senge, Peter. The Fifth Discipline: The Art andP
ractice of the Learning Organization. Doubleday,1990.
Shishko, Robert, Donald H. Ebbeler, and George Fox. NASA Technology Assessment Using RealOptions Valuation, Systems Engineering7(1), 2004, 1-12.
Tenner, Edward . Why Things Bite Back: Technology and the Revenge of Unintended Consequences.Knopf, 1997
Waldrop, Michael. Complexity: The Emerging Science at the Edge of Order and Chaos. New York:
Touchstone, 1992.