Complexity: Ch. 1 Complexity in Systems 1. Broad Examples Insect colonies The brain The immune system Economies The World-wide Web Complexity in Systems.

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Presentation transcript:

Complexity: Ch. 1 Complexity in Systems 1

Broad Examples Insect colonies The brain The immune system Economies The World-wide Web Complexity in Systems 2

Breaking Ranks Temporarily We’re going to leave the book’s systematic development for a while and take a closer look at one particular type of complex system. This will give us a chance to introduce several topics that will be continuing themes in the course. And it’s sometimes more interesting. Complexity in Systems 3

Eusocial Animals Highly evolved level of organization cooperative care for immature members multiple generations in a colony both reproductive and non- reproductive members Complexity in Systems 4

Some Eusocial Animals Complexity in Systems 5 naked mole rat parasitic shrimp ants bees wasps termites

Eusocial Insects 1.9 million animal species described so far probably 8-30 million total about one half are insects: 4-15 million about 1% are eusocial: 100,000 Complexity in Systems 6

Eusocial Insects Dominant role in most land ecosystems Ultimate superorganisms principal predators principal scavengers aerate soil food for other animals Complexity in Systems 7

Ants Entire colony is a single superorganism on which evolutionary selection operates. organizations vary greatly number of queens size of colony, including supercolonies of several hundred million members reproductive practices foraging practices Complexity in Systems 8

I’d like you to meet a young lady from a very interesting family Complexity in Systems 9 A member of a eusocial ant species

Attine Distribution tropical regions of Mexico, Central America, South America, southern U.S. as far north as the New Jersey Pine Barrens as far south as central Argentina Attines appear to have a single ancestor species: agriculture in the New World was probably invented just once, shortly after South America separated from Africa. Leafcutter Ants 10

Attine Agriculture human agriculture about 10,000 years ago attine agriculture about 60 million years ago (six thousand times more ancient) fungus agriculture developed by termites in the Old World attine (leafcutter) ants in the New World Complexity in Systems 11

Atta cephalotes (Costa Rica) Complexity in Systems 12

Complexity in Systems 13

Atta Texana Nest Model Complexity in Systems 14

Complexity in Systems 15 Colombia: $40/lb

To see a live leafcutter colony cross the bridge into Vermont, turn left, and visit Complexity in Systems 16

How Do Attine Colonies Work? Good question Intensely studied We’re going to look at a few models Complexity in Systems 17

Complexity in Systems 18 All models are wrong but some are useful. - George Box, 1976

Two broad motives for modeling One is to accurately represent reality: Complexity in Systems 19

Two broad motives for modeling The other is to discover the origins of some essential features of reality Complexity in Systems 20

Which is what we’ll do here Agent-based Modeling Create a world with a bunch of ants (agents) in it Assign behavioral rules to the ants Start the clock ticking Complexity in Systems 21

Ant Rules If she has food and is at the nest drop off the food. Otherwise if she has food head for the nest. Otherwise if she finds food pick up a piece. Otherwise wander randomly around. Complexity in Systems 22

The Universe Complexity in Systems 23

Early days in the Universe Complexity in Systems 24

Complexity in Systems 25 Now let’s take a look at some simulations in NetLogo

What have we seen? Individual ants have very small behavioral repertoire A small set of rules leads to the emergence of “coordinated” behavior Information exchange (chemical trails) increases efficiency Complexity in Systems 26

Properties of Complex Systems Complex collective behavior Information processing Adaptation Complexity in Systems 27

Mitchell’s Definition A complex system is one in which large networks of independent components with simple rules create complex collective behavior information processing systems adaptive change Complexity in Systems 28