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Swarm Theory And Web Communities
Swarm Theory traces its roots back to the 1940s in a conjecture by John Von Neumann that there might be a self-replicating automaton. British mathematician John Conway simplified Von Neumann’s solution with “The Game of Life” (which has no connection to the Milton Bradley board game of the same name).
Conway’s game uses a small set of very simple rules for turning cells on or off within a grid structure. The game launched a revolution in artificial intelligence and the study of cellular automata. However, it would not be until scientists began figuring out ways to replicate ant behavior in business scheduling processes that people would see the connection between the simple math rules of “The Game of Life” and Swarm Theory.
Swarm Theory proposes that large groups of simple intelligences can solve complex problems very efficiently. You might stop to ask if that means the human brain is a swarm of simple intelligences working together. The question has indeed occurred to a number of people.
Conway’s game uses a small set of very simple rules for turning cells on or off within a grid structure. The game launched a revolution in artificial intelligence and the study of cellular automata. However, it would not be until scientists began figuring out ways to replicate ant behavior in business scheduling processes that people would see the connection between the simple math rules of “The Game of Life” and Swarm Theory.
Swarm Theory proposes that large groups of simple intelligences can solve complex problems very efficiently. You might stop to ask if that means the human brain is a swarm of simple intelligences working together. The question has indeed occurred to a number of people.
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Published March 26, 2009
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January 5, 2022Here are three examples of how the process works:
Ants find the richest food source by following the strongest pheromone trail, which is laid down by the largest number of ants following the same path.
Bees choose a new hive location on the basis of which potential new hive location first attracts 15 advocates.
Fish and Elk evade predators by fleeing in as many directions as possible, thus overwhelming the predators’ abilities to choose from many targets.
Ants find the richest food source by following the strongest pheromone trail, which is laid down by the largest number of ants following the same path.
Bees choose a new hive location on the basis of which potential new hive location first attracts 15 advocates.
Fish and Elk evade predators by fleeing in as many directions as possible, thus overwhelming the predators’ abilities to choose from many targets.
Displaying 1 of 1 review