John Holland was born in 1929 in Indiana and raised in western Ohio. At a young age John had a craving for knowledge. Academically, physics and mathematics, were his strengths. During his senior year in highschool he took a state wide exam in these two subjects and missed first place by 2 points. He finished third and this got him a full scholarship to MIT. This is where he began to emplore the simulation of natural evolution to computers. "It would be twenty years before John Holland settled on it and twenty more years before people began to understand its significance." Holland received the first PhD in Computer Science. He was fascinated by a programming based on constricting artificial networks of metaphorical neurons (which is the idea that neurons came together to form a network from which created memories and complex behavior emerged). This worked well with Hollands ideas on artificial life.
Holland became an expert in computer programming and IBM asked him to work with an elite group of engineers, planning logical design of the companies first calculator the "701". To test the 701 they implemented a nerve-net system and used the computer as a lab rat. "Even then we understood there were real advantages of having these simulated test animals. The advantage was that we go inside and see individual neurons, start the thing over from the same initial conditions and go through a different training routine."
As Holland saw it, there was a link between biology and computation. Machines could be trained to adapt to surroundings the same way animals could. Bottom up. Bottom up "Starts with a virtual randomness and program nature into it." A book titled "The Genetic Theory of Natural Selection" , changed Holland's life. The book saw evolution as an engine for adaptation. "Evolution was like learning a form of adapting to the environment. It worked over generations, rather than a single life span." He thought if this theory could work so well for organisms, why not computer programs as well. This is where Holland imposed the theory of GA. "A Genetic Algoithm is a method of problem analysis based on Darwin's theory of natural selection. It starts with an initial population of individual nodes, each with randomly generated characteristics. Each is evaluated by some method to see which ones are more successful. These successful ones are then merged into one" child "that has a combination of traits of the parents characteristics." This was a very brilliant step for Holland. "Genetic algorithms were a breakthrough in two respects:1. they utilized evolution to provide a powerful way to perform optimization functions on a computer and2. provide window for the workings of evolution and a unique manner of studying natural phenomena."
From Genetic algorithms came what Holland called "schema theorem". Holland looked at "Fisher's theorem and saw it applied to individual genes. The schema theorem expanded how buiding blocks exerted their powers in GAS and indicated what might be a basis for populationwide retention of genes in natural biology." Schema is used to refer to similarity template used to describe all strings that contained a given building block or set of building blocks. The key principle is proximity. Proximity is power in building blocks.
Holland was asked to be an external faculty member at the Santa Fe Institute. There are no internal workers. The institute is a complex think tank. "The Santa Fe Institute is a private, non-profit, multidisciplinary research nd education center, founded in1984. ...It has devoted itself to creating a new kind of scientific research community, pursuing emerging science." These are some of the most important accomplishments given to us by John Holland.