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Transcript of New Mexico Computer Science for All Exploring Complex Systems through Computer Models By Irene Lee...
New Mexico Computer Science for All
Exploring Complex Systems through Computer ModelsBy Irene LeeDecember 27, 2012
Introduction to complex systemsWhat are theyWhy do we study themHow do we study them
Outline
What is a complex system?
Complex (adj.)difficult-to-understand or difficult to predict
System (noun)A group of interacting, interrelated, or interdependent parts forming a whole.
A “Complex System”is collections of simple units or agents interacting in a system. Large-scale behaviors of the system are difficult to understand or difficult to predict and may change, evolve, or adapt.
Characteristics of Complex Adaptive Systems
Leaderless (a.k.a. decentralized)
Characteristics of Complex Adaptive Systems
A classic exampleBirds Flocking
A classic exampleflocking - Craig Reynolds
Separation: steer to avoid crowding local flockmates
Alignment: steer towards the average heading of local flockmates
Cohesion: steer to move toward the average position of local flockmates
http://www.red3d.com/cwr/boids/
A classic exampleBoids - Craig Reynolds
http://www.red3d.com/cwr/boids/
Emergent patterns develop from the simple interactions of agents
Characteristics of Complex Adaptive Systems
A classic exampleTermites
Termites model
A classic exampleMound building in StarLogo TNG
Non-linear The sum of the parts is not equal to the whole.
Characteristics of Complex Adaptive Systems
In Mathematics
Non-linear means: f(a+b) f(a) + f(b)
Ex.) the exponential function is non-linear.
f(2 + 3) f(2) + f(3) f(5) f(2) + f(3)
25 4 + 9 *Non-linear systems are systems that cannot be mathematically
described as the sum of their components.
Self-organization The system organizes itself.
Characteristics of Complex Adaptive Systems
A classic exampleSchelling Segregation Model
Developed by Thomas C. Schelling(Micromotives and Macrobehavior, 1978).
A classic exampleSchelling Segregation Model
1. Leaderless there is no leader (boids)
2. Emergent patterns develop from the simple interactions of agents. (termites)
3. Non-linear The sum of the parts does not equal the whole.
4. Self-organization The system organizes itself
4 Characteristics of Complex Adaptive Systems
Why is it important to learn about complex systems and
approaches to understanding complex systems?
Climate change Loss of biodiversity Pollution Civil violenceSpread of disease Emergency Egress Traffic jams Forest fire
Many of the daunting problems of the 21st Century can be studied as complex
systems problems.
Epidemics
Hufnagel, L. et al. 2004 PNAS 101:15124 Forecast and control of epidemics in a globalized worldCopyright ©2004 by the National Academy of Sciences
NATURE|Vol 460|6 August 2009
Epidemics
Networks
upload.wikimedia.org/.../Internet_map_4096.png
Ocean Circulation - Ecosystems
Transportation Systems
Workflow Simulation
Crowd Dynamics
Crowd Dynamics
Crowd Dynamics
We will learn about agent-based modeling and simulation as an
approach to understanding complex systems
The Computational Science Process
NetLogo is a tool used to create a Computational Model
Begin here