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The Interesting In Between: Why Complexity Exists. Scott E Page University of Michigan Santa Fe Institute scottepage@gmail.com. Background Reading. Outline. Attributes Properties The Interesting In Between Why Complexity Conclusions. Complex Adaptive Systems: Attributes.
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The Interesting In Between: Why Complexity Exists Scott E Page University of Michigan Santa Fe Institute scottepage@gmail.com
Outline Attributes Properties The Interesting In Between Why Complexity Conclusions
Complex Adaptive Systems Networks Source: MIT
Complex Adaptive Systems Networks Adaptation Source: Exploring Nature
Complex Adaptive Systems Networks Adaptation Interactions Source: Uptodate.com
Complex Adaptive Systems Networks Adaptation Interactions Diversity Source: Scientific American
Complex ≠ Chaos Source: Andrew Russell
Complex ≠ Difficult Source: Biology-direct
Complex = Dancing Landscapes Source: Chris Lucas
Epi-Phenomena Emergence Structures and Levels Source: Boortz.com
Diffusion Limited Aggregation Start with a seed on a plane. Create drunken walkers who start from a random location and walk in random directions until touching the seed, at which point the walkers become immobilized. Witten and Sander (1981)
Diffusion Limited Aggregation seed walker
Conway’s Game of Life Cell has eight neighbors Cell can be alive Cell can be dead Dead cell with 3 neighbors comes to life Live cell with 2,3 stays alive 2 3 1 4 X 5 8 6 7
Examples X
A New Kind of Science - Wolfram Binary state objects arranged in a line using simple rules can create - “perfect’’ randomness - chaos - patterns - computation
Epi-Phenomena Emergence Structures and Levels Emergent Functionalities Source: Biology-direct
Wolfram’s 256 Automata N X N X
Rule 90 N X N X 2 8 16 64 Sum = 90
Rule 90 N X N X 2 8 16 64 Sum = 90
Emergent Computation Source: U of Indiana
Epi-Phenomena Emergence Structures and Levels Emergent Functionalities Innovation http://media-2.web.britannica.com/eb-media/54/4054-004-F5EB3891.jpg
Epi-Phenomena Emergence Structures and Levels Emergent Functionalities Innovation Large Events
A Long Tailed Distribution cities size words citations web hits book sales phone calls earthquakes moon craters wars net worth family names
Large Events Source: www2002
Per Bak’s Sandpile sand table floor
Per Bak’s Sandpile sand table floor
Self Organized Criticality Systems may self organize into critical states. If so “events” may not be normally distributed. They may instead have long tails. Small events could have enormous consequences.
Epi-Phenomena Emergence Structures and Levels Emergent Functionalities Innovation Large Events Robustness Source: NBC
“Imagine how difficult physics would be in electrons could think.” -Murray Gell-Mann
Robustness: The World of Thinking (or adapting) Electrons
A Thought Play A Simple Model of Forest Fires & Bank Failures
The Bank Model Banks choose to make a risky loan each period with probability p
The Bank Model Banks choose to make a risky loan each period with probability p Risky loans fail with probability q but have a higher yield
The Bank Model Banks choose to make a risky loan each period with probability p Risky loans fail with probability q but have a higher yield Failures spread to neighboring banks only if those banks have a risky loan outstanding
The Forest Fire Model Trees choose to make a grow each period with probability p Trees get hit by lightening with probability q Fire spreads to neighboring locations only if those locations have a tree
Example Period 1: 00R00R000RR0R Period 2: R0R00R00RRRRR
Example Period 1: 00R00R000RR0R Period 2: R0R00R00RRRRR Period 3: R0R00R00FRRRR Period 4: R0R00R00FFFFFF Period 5: R0R00R00000000
Key Insight Revisited Bank managers should be smarter than trees!
Forest Fire Model Results Yield increases in p up to a point and then falls off rather dramatically Physicists call this a ``phase transition’’