Complexity John Paul Gonzales Santa Fe Institute // Project GUTS / Supercomputing Challenge Betsy Frederick Silicon Desert Consulting // Project GUTS

Complexity

John Paul GonzalesSanta Fe Institute // Project GUTS / Supercomputing Challenge

Betsy FrederickSilicon Desert Consulting // Project GUTS / Supercomputing Challenge

[email protected]

Scientifically Connected Communities31 May 2011 and 20 June 2011

Complexity: Agenda/Outline“Sunday Morning Thoughts”

HistoryDefinitions

via history and student examplesFields

“Monday Morning Ideas”Paradigm Shift in ScienceImplications for Science Education – Computational ThinkingClassroom Tools

Definitions

Complexity

…No Easy Definition.

Yet.

Definitions

“An intelligence which, at a given instant knew all the forces acting in nature and the position of every object in the universe – if endowed with a brain sufficiently vast to make all necessary calculations – could describe with a single formula the motions of the largest astronomical bodies and those of the smallest atoms.

To such an intelligence, nothing would be uncertain; the future, like the past, would be an open book.

“A Philosophical essay on Probabilities,” 1795-Pierre-Simon Laplace

Definitions

Age of Determinism

Definitions

Age of Determinism

Definitions

Flickr.com/practicalowl

Definitions

Definitions

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…But Does It Work?

Does it Work?

Yes:

http://www.grc.nasa.gov/

Does it Work?

Yes:

=

But what about flocking?

Does it Work?

No.

Flickr.com/FininEden

“Whole is greater than the sum of its parts.”

“Whole is greater than the sum of its parts”

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Reynolds, 1986

Complexity:(My Definition)

“The study of (large) systems made up of simple parts that, when following simple rules, produce, collective, unpredictable, and emergent behavior.”

“Whole is greater than the sum of its parts.”

“Have to play the game to see the outcome.”

Let’s look at Boids.

What opportunities does a model like this offer us?

Inquiry - What if?

Science talk

Experiments

Students can build their own models based on examples.

Complex Systems

Computer models are used by scientists to understand complex systems and possibly prevent (or study interventions for) daunting problems such as epidemics and other problems that define the 21st century. Climate change, loss of biodiversity, energy consumption and virulent disease affect us all (Emmott et al., 2006). (Irene Lee)

http://www.nsf.gov/news/mmg/media/images/crowded_world1_h.jpg

Emergency Egress Model: Think of school emergency exit plans.

Melanie Mitchell asks, How … do insect colonies, composed of thousands to millions of individual insects, collectively make decisions and accomplish complex tasks that seem to require the communication and processing of colony‐wide information? How does the immune system, composed of trillions of cells and molecular components circulating in the body, collectively recognize patterns of infection and other organism‐wide conditions, and collectively decide how to mount an appropriate response?

One good illustration of this is the process of task allocation in ant colonies. In an ant colony, ants take on different specialized tasks, such as foraging for food, nest maintenance, patrolling the nest, and refuse‐sorting. Ants do not always stick to the same task; instead they often switch tasks as needed, depending on the current state of their environment. Each ant has a limited view of the global nest environment, limited contact with other ants, and no central “controller” issuing commands as to what task to pursue. How do ants decide what task to take on at a given time so that the colony as a whole will have an optimal allocation of workers to various tasks, given that the optimal allocation continually changes?  

Monday Morning

Why do I want to do this?

Why do I want to do this?

It’s powerful.

Why do I want to do this?

It’s intuitive.

Vs.

Lotka-Volterra Competition Model

Why do I want to do this?

It’s intuitive.

Vs.

Lotka-Volterra Competition Model

Wolves/Sheep ABM

Find this example in the NetLogo Library

Complex Systems are sometimes called Complex Adaptive Systems

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Many agents following simple rules

Leaderless

Emergent, self-organizing behavior

Dynamic environment

Difficult to predict

Time for one more example?

A “Times Change” Observation

Adding in Roman Numbers:

I, V, X, L, C, D, MIV, IX, XL, XC CD, CM…

Adding in Roman Numbers (http://turner.faculty.swau.edu/mathematics/materialslibrary/roman/)

CCCLXI + DCCCXLVCCCLXVIII + DCCCXXXVDCCCCCCLXXXXXVVIIIIDCCCCCCLLXIIIIDCCCCCCCXIIIIDCCXIIIIMCCCXIIIIMCCXIV

OR: 369 + 845 = 1214

References/ReadingsEpstein, Joshua. “Why Model?”Lecture, 2008.

http://www.mit.edu/~scienceprogram/Materials/Monday%20Materials/WhyModel.pdf

Johnson, George. “All Science is Computer Science” New York Times, 2001. http://www.cs.iastate.edu/all-science-is-cs.html

Mitchell, Melanie. Complexity, A Guided Tour. Portland University Press, 2009.

Mitchell, Melanie. What is Computation? Bilolgical Computation. ACM Ubiquity Symposium. http://web.cecs.pdx.edu/~mm/BiologicalComputation.pdf

Netogo can be downloaded from Northwestern University

Supercomputing Challenge: http://challenge.nm.org

Project GUTS: http://projectguts.org

A “Real World” Example

Wolves and Sheep

“Have to play the game to see the outcome.”

IterationRandomness/Chance

Evolution over Time

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