Holland Biography

John Henry Holland is a Professor of Psychology at Johns Hopkins University, a leading career guidance expert in the United States, and a recipient of the prestigious MacArthur Research Fellowship, a member of the MacArthur Society and the World Economic Forum, and one of the chairpersons of the Steering Committee of the Santa Fe Institute.

His main research areas are complex adaptive systems, and computer modeling of cognitive processes.

John Hollander was born in Indiana in 1929 and grew up in western Ohio. At a young age, John showed a strong desire to learn. He was very good at math and physics. In his senior year of high school, he finished third in the statewide math and science exams, just two points below the first-place finisher, and won a full scholarship to attend the Massachusetts Institute of Technology. Since then, he has been on a quest to use computers to simulate biological evolution in nature. "This research took him two decades to come to fruition, and it took people more than two decades before they began to recognize its importance" Hollander's first doctorate was in computer science. He was fascinated by program-based artificial intelligence neural networks (the idea of forming networks of neuron cells that lend themselves to generating memories and complex behaviors) because this approach coincided with his thinking on artificial life intelligence.

John Hollander became an expert in computer programming, and IBM asked him to work with an elite team of engineers on the logical design of the company's first calculator, the '701'. To test the '701', they installed a neural network system on it and used it as a lab rat. "At that point, we knew the advantages of using these analog test animals. We could get inside it and look at every neuron, and we could also start things over again with different training programs under the same initial conditions."

As Hollander sees it, biology and computational science are intimately connected. Machines can be trained to adapt to their surroundings, just like animals. From the bottom up, "start with a virtual random state and write natural characteristics into the program." A book called "The Genetic Principles of Natural Selection" changed Hollander's life. In the book, evolution is seen as self-adaptation of the engine. "Evolution is like a way of learning to adapt to the environment. Evolution is superimposed on sub-generations, not just happening in one life cycle." Hollander believes that if this principle exists in organisms, it could also exist in computer programs. This is what he proposes as a genetic algorithm. "A genetic algorithm is a method of problem analysis based on Darwin's theory of species selection. It starts with a certain number of initial points, each node having randomly generated characteristics, and some method is used to evaluate which nodes have a high success rate. Successful nodes are merged to generate children, who thus have the characteristics of both parents." This is a brilliant step in Hollander's algorithm. "The genetic algorithm is a breakthrough in two ways: first, it uses evolutionary ideas to provide powerful methods to optimize computer functions, and second, it provides a space to study evolution and a unique way to study natural phenomena."

From genetic algorithms developed Hollander's pattern theorem. Hollander found that it was possible to apply Fischer's principle to individual genes. Schema theorem expanded how buiding blocks exerted their powers in GAS and indicated what might be a basis for populationwide retention of genes in 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.

Hollander was invited to serve as an external faculty member at the Santa Fe Institute, which has no full-time faculty. The college is like a complex repository of ideas. "Founded in 1984, the Santa Fe Institute is a private, nonprofit, multidisciplinary educational and research institution dedicated to creating a new kind of research community that explores emerging topics." Some of the most important accomplishments Hollander has made in these areas.

Major Contributions

John. Hollander in 1959 introduced the theory of human-industrial interactions, which has had a wide social impact. This theory firstly classifies workers into six basic types according to their psychological qualities and career choice tendencies, and the corresponding occupations are also classified into six types: social, corporate, routine, practical, research and artistic.

The essence of Hollander's theory of career choice lies in the mutual adaptation of laborers and careers. According to Hollander, the same type of labor and occupation combined with each other, is to achieve the state of adaptation, as a result, the worker to find suitable occupational positions, their talents and motivation will be able to play well.

[edit]Major publications

Adaptation in Natural and Artificial Systems (1975,1992) (the seminal work on genetic algorithms)

Hidden Order: How Adaptation Builds Complexity Hidden Order: How Adaptation Builds Complexity (1995)

Emergence: From Chaos to Order (1998)

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