The synthetic path to investigating the world is the logical space occupied by the physicist Murray Gell-Mann, the biologist Stuart Kauffman, the computer scientist Christopher G. Langton, and the physicist J. Doyne Farmer, and their colleagues in and around Los Alamos and the Santa Fe Institute.
The Santa Fe Institute was founded in 1984 by a group that included Gell-Mann, then at the California Institute of Technology, and the Los Alamos chemist George Cowan. Some say it came into being as a haven for bored physicists. Indeed, the end of the reductionist program in physics may well be an epistemological demise, in which the ultimate question is neither asked nor answered but instead the terms of the inquiry are transformed. This is what is happening in Santa Fe.
Murray Gell-Mann, widely acknowledged as one of the greatest particle physicists of the century (another being his late Caltech colleague, Richard Feynman), received a Nobel Prize for work in the 1950s and 1960s leading up to his proposal of the quark model. At a late stage in his career, he has turned to the study of complex adaptive systems.
Gell-Mann's model of the world is based on information; he connects the reductionist, fundamental laws of physics — the simple rules — with the complexity that emerges from those rules and with what he terms "frozen accidents" — that is, historical happenstance. He has given a name to this activity: "plectics," which is the study of simplicity and complexity as it is manifested not just in nature but in such phenomena as language and economics. At the institute, he provides encouragement, experience, prestige, and his vast reservoir of scientific knowledge to a younger group of colleagues, who are mostly involved in developing computational models based on simple rules that allow the emergence of complex behavior.
Stuart Kauffman is a theoretical biologist who studies the origin of life and the origins of molecular organization. Twenty- five years ago, he developed the Kauffman models, which are random networks exhibiting a kind of self-organization that he terms "order for free." Kauffman is not easy. His models are rigorous, mathematical, and, to many of his colleagues, somewhat difficult to understand. A key to his worldview is the notion that convergent rather than divergent flow plays the deciding role in the evolution of life. With his colleague Christopher G. Langton, he believes that the complex systems best able to adapt are those poised on the border between chaos and disorder.
Kauffman asks a question that goes beyond those asked by other evolutionary theorists: if selection is operating all the time, how do we build a theory that combines self-organization (order for free) and selection? The answer lies in a "new" biology, somewhat similar to that proposed by Brian Goodwin, in which natural selection is married to structuralism.
Christopher G. Langton has spent years studying evolution through the prism of computer programs. His work has focused on abstracting evolution from that upon which it acts. He has created "nature" in the computer, and his work has given rise to a new discipline called AL, or artificial life. This is the study of "virtual ecosystems," in which populations of simplified "animals" interact, reproduce, and evolve. Langton takes a bottom-up approach to the study of life, intelligence, and consciousness which resonates with the work of Marvin Minsky, Roger Schank, and Daniel C. Dennett. By vitalizing abstraction, Langton hopes to illuminate things about life that are not apparent in looking at life itself.
J. Doyne Farmer is one of the pioneers of what has come to be called chaos theory — the theory that explains why much of nature appears random even though it follows deterministic physical laws. It also shows how some random-seeming systems may have underlying order which makes them more predictable. He has explored the practical consequences of this, showing how the game of roulette can be beaten using physics; he has also started a company to beat the market by finding patterns in financial data.
Farmer was an Oppenheimer Fellow at the Center for Nonlinear Studies at the Los Alamos National Laboratory, and later started the complex systems group, which came to include some of the rising stars in the field, such as Chris Langton, Walter Fontana, and Steen Rasmussen. In addition to his work on chaos, he has made important theoretical contributions to other problems in complex systems, including machine learning, a model for the immune system, and the origin of life.
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