p.13 Now I can propose a definition of the term complex system: a system in which large
networks of components with no central control and simple rules of operation give rise to complex collective behavior, sophisticated
information processing, and adaption via learning or evolution... Here is an alternative definition of complex
system: a system that exhibits nontrivial emergent and self-organizing behaviors.
p.15-16 Dynamical systems theory (or dynamics) concerns the description and prediction
of systems that exhibit complex changing behavior at the macroscopic level, emerging from the collective actions
of many interacting components. The word dynamic means changing, and dynamical systems are systems that
change over time in some way... Dynamical systems theory describes in general terms the ways in which systems can change,
what types of macroscopic behavior are possible, and what kinds of predictions about that behavior can be made.
p.38-39 idea models - models that are simple enough to study via mathematics or computers but that
nonetheless capture fundamental properties of natural complex systems. Idea models play a central role in this book, as they
do in the sciences of complex systems.
p.39 Characterizing the dynamics of complex systems is only one step in understanding it.
p.71 All great truths begin as blasphemies.
-George Bernard Shaw, Annajanska, The Bolshevik Empress
p.72 The Philosopher Daniel Dennett [says] If I had to give an award for the single best idea anyone
has ever had, I'd give it to Darwin, ahead of Newton and Einstein and everyone else. In a single stroke, the idea
of evolution by natural selection unifies the realm of life, meaning and purpose with the realm of space and time, cause and
effect, mechanism and physical law.
p.78 Unbeknown to Darwin, twenty-eight years before publication of the Origin, a little-known Scot
named Patrick Matthew had published an obscure book with an equally obscure title, On Naval Timber and Arboriculture,
in whose appendix he proposed something very much like Darwin's evolution by natural selection.
p.79 According to this view [JLJ - a summary of the ideas of Darwin], the result of evolution by
natural selection is the appearance of "design" but with no designer. The appearance of design comes from chance,
natural selection, and long periods of time. Entropy decreases (living systems become more organized, seemingly more designed)
as a result of the work done by natural selection. [JLJ - this concept can explain how a relatively unintelligent computer
can "design" a plan in a game, when supplied with instructions on how to manipulate a dynamic model and how to interpret the
results. Intelligent behavior therefore results from a model, a procedure, and the evolution of a design via an executor of
a strategic plan.]
p.85 Historical contingency refers to all the random accidents, large and small, that have contributed
to the shaping of organisms.
p.87 Gould, Eldredge, and others... like virtually all biologists, still strongly embrace the basic
ideas of Darwinism: that evolution has occurred... that all modern species have originated from a single ancestor;
that natural selection has played an important role in evolution; and that there is no "intelligent" force directing
evolution or the design of organisms.
p.94 If the faculty of the Santa Fe Institute - the most famous institution in the world devoted to research
on complex systems - could not agree on what was meant by complexity, then how can there even begin to be a science
of complexity?
p.170 At a very general level, one might say that computation is what a complex system
does with information in order to succeed or adapt in its environment.
p.182 Many, if not all, complex systems in biology have a fine-grained architecture, in that they consist
of large numbers of relatively simple elements that work together in a highly parallel fashion.
Several possible advantages are conferred by this type of architecture, including robustness, efficiency,
and evolvability. One additional major advantage is that a fine-grained parallel system is able to carry out what Douglass
Hofstadter has called a "parallel terraced scan." This refers to a simultaneous exploration of many possibilities or pathways,
in which the resources given to each exploration at a given time depend on the perceived success of that exploration at that
time. The search is parallel in that many different possibilities are explored simultaneously, but is "terraced"
in that not all possibilities are explored at the same speeds or to the same depth. Information is used as
it is gained to continually reassess what is important to explore. [JLJ - important concept for a machine playing
a game, such as chess]
p.182 Similarly, ant foraging uses parallel-terraced-scan strategy: many ants initially
explore random directions for food. If food is discovered in any of these directions, more of the system's resources (ants)
are allocated, via the feedback mechanisms described above, to explore those directions further. At all times, different
paths are dynamically allocated exploration resources in proportion to their relative promise (the
amount and quality of the food that has been discovered at those locations). However, due to the large number of ants and
their intrinsic random elements, unpromising paths continue to be explored as well, though with many fewer resources. After
all, who knows - a better source of food might be discovered.
p.183-184 In all three example systems there is a continual interplay of unfocused, random explorations
and focused actions driven by the system's perceived needs... As in all adaptive systems, maintaining a correct balance
between these two modes of exploring is essential. Indeed, the optimal balance shifts over time. Early explorations, based
on little or no information, are largely random and unfocused. As information is obtained and acted on, exploration gradually
becomes more deterministic and focused in response to what has been perceived by the system. In short, the system
both explores to obtain information and exploits that information to successfully adapt. This
balancing act between unfocused exploration and focused exploitation has been hypothesized to be a general property of adaptive
and intelligent systems.
p.209 A model, in the context of science, is a simplified representation of some "real" phenomenon. Scientists
supposedly study nature, but in reality much of what they do is construct and study models of nature.
p.210-211 Models are ways for our minds to make sense of observed phenomena in terms of concepts
that are familiar to us, concepts that we can get our heads around... Models are also a means for predicting
the future... computers are often used to run detailed and complicated models that in turn make detailed predictions
about the specific phenomena being modeled... a major thrust of complex systems research has been the exploration of idea
models: relatively simple models meant to gain insights into a general concept without the necessity of making detailed
predictions about any specific system.
p.222 All models are wrong, but some are useful. - George Box and Norman Draper
p.233,252 Network thinking means focusing on relationships between entities rather than the entities
themselves... network thinking is providing novel ways to think about difficult problems... and, more generally,
what kind of resilience and vulnerabilities are intrinsic ... and how to exploit and protect such systems.
p.273 the closer one looks at living systems, the more astonishing it seems that such intricate complexity could have
been formed by the gradual accumulation of favorable mutations or the whims of historical accident.
p.296 A prime mover of this group [JLJ - The Macy Foundation conferences] was the mathematician Norbert Wiener,
whose work on the control of anti-aircraft guns during World War II had convinced him that the science underlying
complex systems in both biology and engineering should focus not on the mass, energy, and force
concepts of physics, but rather on the concepts of feedback, control, information, communication, and purpose (or
"teleology").
