Presentation is loading. Please wait.

Presentation is loading. Please wait.

New Mexico Computer Science for All Exploring Complex Systems through Computer Models By Irene Lee December 27, 2012.

Similar presentations


Presentation on theme: "New Mexico Computer Science for All Exploring Complex Systems through Computer Models By Irene Lee December 27, 2012."— Presentation transcript:

1 New Mexico Computer Science for All Exploring Complex Systems through Computer Models By Irene Lee December 27, 2012

2 Introduction to complex systems What are they Why do we study them How do we study them Outline

3 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.

4 Characteristics of Complex Adaptive Systems

5 L eaderless (a.k.a. decentralized) Characteristics of Complex Adaptive Systems

6 A classic example Birds Flocking

7 A classic example flocking - 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

8 A classic example Boids - Craig Reynolds

9 E mergent patterns develop from the simple interactions of agents Characteristics of Complex Adaptive Systems

10 A classic example Termites Termites model

11 A classic example Mound building in StarLogo TNG

12 N on-linear The sum of the parts is not equal to the whole. Characteristics of Complex Adaptive Systems

13 In Mathematics N on-linear means: f(a+b) f(a) + f(b) Ex.) the exponential function is non-linear. f(2 + 3) f(2) + f(3) f(2 + 3) f(2) + f(3) f(5) f(2) + f(3) f(5) f(2) + f(3) *Non-linear systems are systems that cannot be mathematically described as the sum of their components.

14 S elf-organization The system organizes itself. Characteristics of Complex Adaptive Systems

15 A classic example Schelling Segregation Model Developed by Thomas C. Schelling (Micromotives and Macrobehavior, 1978).

16 A classic example Schelling Segregation Model

17 1. L eaderless there is no leader (boids) 2. E mergent patterns develop from the simple interactions of agents. (termites) 3. N on-linear The sum of the parts does not equal the whole. 4. S elf-organization The system organizes itself 4 Characteristics of Complex Adaptive Systems

18 Why is it important to learn about complex systems and approaches to understanding complex systems?

19 Climate change Loss of biodiversity Pollution Civil violence Spread of diseaseEmergency Egress Traffic jams Forest fire Many of the daunting problems of the 21 st Century can be studied as complex systems problems.

20 Epidemics Hufnagel, L. et al PNAS 101:15124 Forecast and control of epidemics in a globalized world Copyright ©2004 by the National Academy of Sciences

21 NATURE|Vol 460|6 August 2009 Epidemics

22 Networks upload.wikimedia.org/.../Internet_map_4096.png

23 Ocean Circulation - Ecosystems

24 Transportation Systems

25 Workflow Simulation

26 Crowd Dynamics

27

28

29 We will learn about agent-based modeling and simulation as an approach to understanding complex systems

30 The Computational Science Process NetLogo is a tool used to create a Computational Model Begin here


Download ppt "New Mexico Computer Science for All Exploring Complex Systems through Computer Models By Irene Lee December 27, 2012."

Similar presentations


Ads by Google