John Henry Holland quotes:

Holland's and Kauffman's work, together with Dawkins' simulations of evolution and Varela's models of autopoietic systems, provide essential inspiration for the new discipline of artificial life, This approach, initiated by Chris Langton (1989, 1992), tries to develop technological systems (computer programs and autonomous robots) that exhibit lifelike properties, such as reproduction, sexuality, swarming, and co-evolution.

From the point of view of physics, it is a miracle that [seven million New Yorkers are fed each day] without any control mechanism other than sheer capitalism.

Evolution continually innovates, but at each level it conserves the elements that are recombined to yield the innovations.

Unwrapping occurs when the "solution" is explicitly built into the program from the start.

Particular individuals do not recur, but their building blocks do.

When a new building block is discovered, the result is usually a range of innovations.

With theory, we can separate fundamental characteristics from fascinating idiosyncrasies and incidental features. Theory supplies landmarks and guideposts, and we begin to know what to observe and where to act.

nonlinear interactions almost always make the behavior of the aggregate more complicated than would be predicted by summing or averaging.

Model building is the art of selecting those aspects of a process that are relevant to the question being asked. As with any art, this selection is guided by taste, elegance, and metaphor; it is a matter of induction, rather than deduction. High science depends on this art.

Looking back to data, we can see if the consequences are plausible; looking forward to theory, we can see if general principles are suggested.

The measure of performance of any given agent is the amount of money it accumulates through its actions.

If there is to be a competition, there must be some basis for resolving it. It is also clear that the competition should be experienced based.

This use of building blocks to generate internal models is a pervasive feature of complex adaptive systems.

The recycling of resource by the aggregate behavior of a diverse array of agents is much more than the sum of the individual actions.

The multiplier effect is a major feature of networks and flows. It arises regardless of the particular nature of the resource, be it goods, money, or messages.

If we are to understand the interactions of a large number of agents, we must first be able to describe the capabilities of individual agents.