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Editor's Notes

• #2: In nature, there are fascinating and wonderful group behaviors that seem beyond easy understanding. How do these birds act as one? Is there some governing force that keeps them together? If birds are simple creatures, then how can they manage such a complex coordination task? What purpose do these fascinating formations serve? Questions like these are what we seek to understand and unpack today.Spontaneous Order. Emerges!
• #4: If videos are not allowed, then I will use the above photograph to illustrate the point.In nature, there are fascinating and wonderful group behaviors that seem beyond easy understanding. The power in this picture comes from the fact that this one confused fish has somehow lost his school and is headed in the opposite direction. It is only powerful because schools normally act as one! How do these fish act as one? Is there some governing force that keeps them together? If fish are simple creatures, then how can they manage such a complex coordination task? What purpose do these fascinating formations serve? Questions like these are what we seek to understand and unpack today.
• #5: Get answers not by observing individual, but by observing collective. More precisely how the interactions of the individuals give rise to the collectiveModel them mathematically or on computers
• #6: Complex patterns arise from very simple interactions. Each fish/bird acts with a simple rule. Example, keep in the same direction as my neighbors and don’t bump into them. These rules can give rise to amazing patterns when aggregated to group level.Changing simple parameters has profound effects on a swarm. By controlling only attraction, repulsion, and alignment (how similar a critter’s direction is to that of its neighbors), researcher Iain Couzin induced three different behaviors in a virtual collective, all akin to ones in nature.—Katie M. PalmerSource: WIRED magazine March 19th, 2013
• #7: Complex patterns arise from very simple interactions. Each fish/bird acts with a simple rule. Example, keep in the same direction as my neighbors and don’t bump into them. These rules can give rise to amazing patterns when aggregated to group level.Changing simple parameters has profound effects on a swarm. By controlling only attraction, repulsion, and alignment (how similar a critter’s direction is to that of its neighbors), researcher Iain Couzin induced three different behaviors in a virtual collective, all akin to ones in nature.—Katie M. PalmerSource: WIRED magazine March 19th, 2013
• #8: Critical Mass/Tipping points, regimes shift rapidly from one to another. Small shift in input can give big rise in output. Systems on the “edge of chaos” or “self-organized criticality”. Think of an avalanche.
• #9: Non-living things – physics of inanimate objects
• #10: All well and good, how does this apply to humans? Traffic jam, show tipping points in traffic jams. Explain Helbing’s work
• #11: How does this apply to humans? Humans aren’t fish or birds! Well, humans interact with other humans. In fact our social nature and the size of the groups we interact with are some of our most human defining characteristics. Think of crowds in public places (featured above are crowds at the Kabba in Mecca during Hajj) or traffic jams. Human collectives display behaviors of tremendous interest.
• #13: Now consider that in all the examples above, the entities were all the same, they interacted only with immediate neighbours, and the strength of each interaction was the same. In reality, in many networks (look at picture on left):the entities are different (blue and red nodes), the interact in predefined patterns with entities beyond their immediate neighbors (think friendship networks), and the weight of each interaction is different (the thickness of black lines)Phenomena of greater interest:This gives rise to much more complex sets of interactions and real world interaction patterns may actually look like the picture on the right. Imagine how information and ideas and viruses and behaviors can flow on such a network. If such complex behaviors arose at the group level from a relatively simple interaction pattern, then what hope might we have of predicting group behaviors in complex interaction patterns?
• #14: Now consider that in all the examples above, the entities were all the same, they interacted only with immediate neighbours, and the strength of each interaction was the same. In reality, in many networks (look at picture on left):the entities are different (blue and red nodes), the interact in predefined patterns with entities beyond their immediate neighbors (think friendship networks), and the weight of each interaction is different (the thickness of black lines)Phenomena of greater interest:This gives rise to much more complex sets of interactions and real world interaction patterns may actually look like the picture on the right. Imagine how information and ideas and viruses and behaviors can flow on such a network. If such complex behaviors arose at the group level from a relatively simple interaction pattern, then what hope might we have of predicting group behaviors in complex interaction patterns?
• #15: What about diseases spreading? What about ideas spreading? What about the Arab Spring? These become truly unpredictable?
• #16: Must we throw our hands up? Say everything is irreducably complex? Yes things are difficult to predict.But no! Simplicity lies on the other side of complexity. Plus, appreciate the beauty and wonder.
• #19: Design for Emergence
• #20: ConnectShareDoAdaptMarvel
• #21: ConnectShareDoAdaptMarvel