At this point, Maynard Smith, like many other theorists, was conflating altruism and cooperation. And again, he assumed that the interaction involved altruism. No longer is synergistic selection associated with altruism; the stress is on cooperation as a class of behaviors with a variety of potential payoff distributions. Although inclusive fitness is not required for such interactions to occur, he suggests that relatedness could be a significant facilitator, especially in initiating cooperation.
Moreover, their detailed study of the process of biological complexification in evolution is consistent in its overall vision with the more explicit conceptualization in The Synergism Hypothesis. However, the more recent realization that group selection can also include mutualistic, win-win forms of co-operation which provide differential reproductive advantages to all concerned has greatly strengthened his argument. The causes of synergistic selection, like natural selection, are always situation-specific.
To our knowledge, nobody has ever succeeded in doing so for natural selection, either. Rather, the synergism hypothesis directs our attention to the combined effects produced by things that work together, or cooperate. Accordingly, the synergism hypothesis can be tested in much the same way that the role of natural selection is routinely tested, with hypotheses and analytical tools that are appropriate to a given context.
One important method for verifying the role of synergy in a given case was first suggested by Aristotle to my astonishment in The Metaphysics b; see also a, a. Thus, the removal of one member from a school of drawf herrings might only marginally affect the probability that any of the remaining members will be eaten by a barracuda.
And the loss of one member from a coalition of male lions, or chimpanzees, might or might not tip the scales in subsequent confrontations. On the other hand, if you remove one oarsman from a varsity eight, the chances are that the remaining seven will lose the race. A second method for testing hypotheses about synergistic effects involves comparative studies of various kinds.
Again, if synergistic effects are real and measurable, then it should be possible to demonstrate the differences that they make in a given context. Game theory offers a third method for testing various hypotheses about synergy, as suggested earlier. By removing a language barrier, the term could facilitate cross-disciplinary communication and understanding. Furthermore, in contrast with the bloodless mathematical caricatures that are blind to the functional properties of the phenomenal world, the synergy paradigm draws our attention to the functional aspect of cooperative effects.
As noted earlier, concepts with broad applicability to many different kinds of phenomena may play an important theoretical role in the sciences. The synergy concept provides a framework for integrating the research in various disciplines that may be relevant for understanding the broader causal role of cooperative phenomena in nature and evolution. All scientific concepts are inescapably Procrustean and selective — highlighting certain aspects of the phenomenal world to the exclusion of others. None can be all things to all scientists. The ultimate test is fruitfulness.
By that standard, the concept of synergy would seem to hold promise. Among other things, it offers a theoretical framework which, like the concept of natural selection, can provide a focus for explaining a major aspect of the evolutionary process, namely, the evolution of organized complexity. Indeed, an invigorated science of synergy would shine a spotlight on a fundamental property of the phenomenal world. Equally important, because it is pan-disciplinary and egalitarian in its methodological implications, the concept of synergy could provide a useful bridge between various specialized disciplines.
If synergy can provide functional advantages elsewhere in the phenomenal world, why not also within the scientific enterprise itself. Many books and innumerable scholarly papers have been published on the subject in the past few years, and there is even a new journal, Complexity, devoted to this nascent science.
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This is not to say that the researchers in this area have not been trying to define it. Though useful, it seems to be limited to processes in which there is a logical structure of some sort. An often-cited analogy is water, whose complex physical properties lie between the highly ordered state of ice crystals and the highly disordered movements of steam molecules.
For instance, it seems to exclude the extremes associated with highly ordered or strictly random phenomena, even though there can be more or less complex patterns of order and more or less complex forms of disorder — degrees of complexity that are not associated with phase transitions.
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Indeed, random phenomena seem to be excluded by fiat from some definitions of complexity. Indeed, information theory is notorious for its reliance on quantitative, statistical measures and its blindness to meaning — where much can be made of very few words. The telephone directory for a large metropolitan area contains many more words than a Shakespeare play, but is it more complex? Furthermore, as Elisabet Sahtouris has pointed out on-line communication , the degree of complexity that we might impute to a phenomenon can depend upon our frame of reference for viewing it.
Accordingly, subjective complexity is a highly variable property of the phenomenal world. Perhaps we need to go back to the semantic drawing-board. Complexity is, after all, a word — a verbal construct, a mental image. Some words may be very narrow in scope. Presumably all electrons are alike in their basic properties, although their behavior can vary greatly.
However, many other words may hold a potful of meaning. Indeed, it seems that many theorists, to suit their own purposes, prefer not to define complexity too precisely.
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It tells you about certain fundamental properties that all trees have in common. But it does not tell you whether or not a given tree is deciduous, whether it is tall or short, or even whether it is living or dead. Although there may be some commonalities between a complex personality, a complex wine, a complex piece of music and a complex machine, the similarities are not obvious. Each is complex in a different way, and their complexities cannot be reduced to an all-purpose algorithm. Moreover, the differences among them are at least as important as any common properties.
One of the leaders in the complexity field, Seth Lloyd of MIT, took the trouble to compile a list of some three dozen different ways in which the term is used in scientific discourse. However, this exercise produced no blinding insight. Rather than trying to define what complexity is, perhaps it would be more useful to identify the properties that are commonly associated with the term. At the risk of inviting the wrath of the researchers in this field, we would argue that complexity per se is one of the less interesting properties of complex phenomena. We believe the differences among them, and the unique combined properties synergies that arise in each case, are more important than the commonalities.
There are many well-documented studies that have measured synergistic effects in quantitative terms. To mention a few other examples: Schaller found that capture efficiency captures per chase times and the number of multiple kills achieved by Serengeti lion prides that he studied increased with group size.
Later studies have shown that hunting efficiencies are dependent on a variety of ecological factors, including the size and capabilities of the prey. In the highly social African wild dog Lycaon pictus , overall kill probabilities in hunting forays were found to be greatly superior between 85 and 90 percent to those achieved by less social top carnivores Estes and Goddard Kummer , documented that collective defense in hamadryas baboons Papio hamadryas , as in many other species, greatly reduces the joint risk to each group member of being a victim of predation.
And von Wagner observed that the Mexican desert spiders Leiobunum cactorum , by clustering together in the thousands during the dry season, are able to avoid death by dehydration. Some of the more important of these properties were outlined in a recent paper by biologist George Wald , namely: the remarkable fact that the mass of every atom is concentrated in its nucleons protons and neutrons ; the fortuitous circumstance that proton and electron charges are numerically equal; the unique emergent characteristics of the four basic elements that constitute about 99 percent of living matter hydrogen, carbon, nitrogen and oxygen ; the underappreciated fact that ice floats instead of sinking because water expands as it approaches 0oC.
Indeed, the same kind of anthropic reasoning could be extended to the 3. In any event, the outcome was co-determined; it was dependent upon the entire configuration of preconditions. All were necessary and none were sufficient. The sources of creativity in evolution is an issue that is often kept in the shadows, or even backstage. The insufficiency of these formulations has been apparent to many evolutionists over the years, to the point that some have been led to reject Darwinism altogether, or at least the gene-centered model. The problem is most acute with respect to the evolution of complexity — the intricate functional organization that characterizes even many rudimentary life forms.
How can a temporal sequence of random changes produce complex, synergistic wholes?
In fact, some theorists envision the ultimate elucidation of a law, or laws of evolution e. The question that is begged by the advocates of self-organization is this: Are there sources of novelty — new synergies — that cannot be modelled by a set of partial differential equations? Is creativity a real phenomenon or merely an epiphenomenon — a dynamical attractor or a phase transition in a deterministic historical process?
One problem with the self-organizing paradigm is that it is insensitive to the functional dimension of evolution, many aspects of which are qualitative and cannot even be expressed mathematically.