IDS 101: Why is Everything so Darn Complicated? An Introduction to Complex Systems: Your Librarian

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Why is Everything so Darn Complicated? An Introduction to Complex Systems Course taught by: Daniel Borrero Echeverry Colloquium Associate: Liandra Chapman Suppose you were an alien scientist, freshly entering Earth orbit after a long journey from the planet Anhooie-4. Using your teleporter, you beam an ant (clearly the dominant species on the planet since there are million billion of them!) onboard, so you can study it. You study it carefully, learning everything you can about it. It has 6 legs. It can carry 30 times its own weight. It likes to eat sugar. Your investigation is so in-depth that you can eventually program the replicator in your lab to make your own ants. Then something incredible happens! The ants start building nests! They start working together to form bridges to cross from one lab bench to another! They start signaling each other where to find food! In a panic, you quickly open the airlock, venting the ants into space before they take over your ship. You quickly point your spaceship toward Sector-7 and jump to lightspeed, quickly headed for safer, ant-less planets. Once in the safety of Sector-7, you look over your notes, scratching your head. What just happened? Nothing in your study of the single ant suggested that ants would behave this way!

Ant colonies are a classic example of a self-organizing complex system, where the interactions between the parts of the system lead to collective behaviors that are more complex than the behavior of any of the constituent parts. Other examples of complex systems include cities, power grids, the economy, the Internet, and well… you! In this course we will learn about the tools used by scientists to understand complex systems, including dynamics, chaos, fractals, information theory, and network theory, drawing examples from across the natural and social sciences. While no significant math or computer background is required, we will spend a considerable amount of time learning the quantitative and computational tools used by scientists to study complex systems.

Source: College Colloquium Page

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