The Engine of Complexity: Evolution as Computation
John E. Mayfield
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The concepts of evolution and complexity theory have become part of the intellectual ether permeating the life sciences, the social and behavioral sciences, and, more recently, management science and economics. In this book, John E. Mayfield elegantly synthesizes core concepts from multiple disciplines to offer a new approach to understanding how evolution works and how complex organisms, structures, organizations, and social orders can and do arise based on information theory and computational science.
Intended for the intellectually adventuresome, this book challenges and rewards readers with a nuanced understanding of evolution and complexity that offers consistent, durable, and coherent explanations for major aspects of our life experiences. Numerous examples throughout the book illustrate evolution and complexity formation in action and highlight the core function of computation lying at the work's heart.
tangible example. It is just not possible to write a simple formula for a soufflé. When relationships between numerical input and numerical output can be expressed in mathematical terms, the output can often be calculated. The power of mathematics is that it provides shortcuts. When simple relationships exist, it is often the case that the physical process of interest does not need to be carried out to determine a particular outcome. An example is the calculation of future positions of planets.
cool air above St r u ct u r e f o r F r ee sinks much as in a Bénard cell, but the presence of water vapor changes things. Rising air expands and cools according to the universal gas law. When enough cooling has occurred, water vapor condenses into droplets of liquid water, releasing heat. This heat warms the air, causing it to rise further and cool more as it expands; this in turn causes more condensation and more heat to be released. The rising air is replaced by a continual inflow of warm
size, with small avalanches much more common than large ones. If replotted as the logarithm of avalanche number versus avalanche size, the resulting graph would fit a straight line sloping down to the right. might expect because they “self-organize.” This simply means that some systems naturally progress over time until a critical state is reached. The sand pile provides an easy-to-visualize example; the critical state is poised at a balance point where one more grain of sand might cause an
used in the world today. Another useful feature of the decimal system is that it can represent numbers that are too large or too small to ever be encountered in our everyday world. Thus, as I write this sentence, the number of human beings on the planet Earth is estimated to be seven billion, seventy-two million, five hundred and seven thousand, three hundred and two, or 7,072,507,302 (and increasing at the rate of three per second). The accumulated deficit of the U.S. government on October 13,
of antigens, both self and nonself, that are potentially recognizable by the adaptive immune system is extremely large—far larger than the number of connections in the brain. So, for many years the central question of immunology was, how can antibodies (and T-cell receptors) be produced that specifically recognize any conceivable foreign protein or polysaccharide that might come along when the number of such structures is effectively infinite? Part of the answer that has unfolded over the past