Preface Emergence is now one of the liveliest areas of research in both science and philosophy.
This activity holds out great promise for understanding a wide variety of phenomena in ways that are intriguingly different
from more traditional approaches.
p.10 The conceptual approach [JLJ - to emergent phenomenon] maintains that a system that has reached
a critical level of complexity can be described effectively only by introducing a conceptual or descriptive apparatus that
is new compared to what is used for more basic phenomena... The impossibility of understanding the phenomena without
this new framework is taken to be the mark of an emergent level of phenomena.
p.11 For [John Stewart] Mill [JLJ - writing in A System of Logic, 1843], emergence was
associated with the failure of the principle of the composition of causes, which states that the effects of causes are additive.
p.13 Irreducibility is one of the leading ideas about emergence; a failure to be reduced often is viewed
as a necessary condition for something to be emergent. Reduction can mean a variety of things, but one standard view is that
a phenomenon has been reduced if it has been explained in terms of phenomena that are more fundamental (according to some
ordinary criterion) than the original phenomenon.
p.15 [Mark] Bedau... defends weak emergence as a nonmysterious and scientifically explainable kind of phenomenon
that arises in certain complex systems.
p.16 The inability to predict theoretically how a process will develop over time also lies at the
heart of what was called weak emergence... In essence, a phenomenon is weakly emergent
if it is produced by lower-level phenomena but there are no theoretical shortcuts to predicting it exactly because the lower-level
process that produces it is computationally irreducible
p.16 The sort of unpredictability that is due to computational irreducibility... is interesting
in part because it is an objective mathematical property of certain complex systems. Promise of a positive answer
to this question resides in the lively area of contemporary research generally known as computational complexity
p.85 [theologian Samuel] Alexander's main idea is that a certain complex configuration of elements of a
given level may possess capacities to produce certain types of effects that are, in [John Stewart] Mill's sense, heteropathic
[JLJ heteropathic: unusual or abnormal] relative to the elements in the configuration. Qualities emerge from the configuration,
and the configuration is governed by special laws of behavior not derivative from the laws that govern behavior at lower
levels of organizational complexity.
p.100 An emergent property is - roughly - a system property which is dependent upon the mode of
organization of the system's parts... the organization of a system's parts provides heuristic ways of evaluating
decompositions which can help us understand why some decompositions are preferred over others
p.101 Emergence involves some kind of organizational interdependence of diverse parts, but there are many
possible forms of such interaction, and no clear way to classify them. It is easier to discuss the failures of emergence (Wimsatt
1986), by figuring out what conditions should be met for the system property not to be emergent - for it to be a "mere aggregate"
of its parts' properties.
p.101 aggregativity - the non-emergence of a system property relative to properties of its parts
(Wimsatt 1986).
p.105-106 We usually evaluate aggregativity relative to assumed constraints on how components
are rearranged or treated - but often forget the constraints. When we do so, we underestimate how much system properties
depend upon how the parts are organized... Blindness to assumed constraints is common.
p.106 Different conditions may be met separately for some decompositions of a given system, but not for
others, and with varying degrees of accuracy. This has critical importance in theory construction: it allows implicit
use of these criteria as heuristics in evaluating decompositions of a system for further analysis. We look for invariances.
p.107 Very few system properties are aggregative, suggesting that emergence, defined as failure
of aggregativity, is extremely common - the rule rather than the exception.
p.127 It has been about a century and half since the ideas that we now associate with emergence began taking
shape. At the core of these ideas was the thought that as systems acquire increasingly higher degrees of organizational
complexity they begin to exhibit novel properties that in some sense transcend the properties of their constituent parts,
and behave in ways that cannot be predicted on the basis of the laws governing simpler systems.
p.158 The constituent molecules in a cup of water, considered individually, cannot have properties like
fluidity or transparency, though these properties do apply to the whole cup of water.
This contrast illustrates a core component of all three kinds of emergence: the notion of
a kind of property that can be possessed by macro objects but cannot be possessed by micro objects.
p.158 The notion of nominal emergence is very broad. It applies to a large number of intuitive examples
of emergent phenomena and corresponds to the compelling picture of reality consisting of a hierarchy of levels... it applies
to all macro-level properties that are not possessed by micro-level entities.
p.160 Weak emergence refers to the aggregate global behavior of certain systems. The system's global behavior
derives just from the operation of micro-level processes, but the micro-level interactions are interwoven in such
a complicated network that the global behavior has no simple explanation. The central idea behind weak emergence
is that emergent causal powers can be derived from micro-level information but only in a certain complex way... Weakly emergent
macro phenomena clearly depend on their underlying micro phenomena... weak emergence presumes causal fundamentalism.
p.164 So-called "agent-based"... simulations in complexity science... explicitly represent micro
interactions, with the aim of seeing what implicit macro phenomena are produced when the micro interactions are aggregated
over space and iterated over time... Natural systems compute their future behavior by aggregating the relevant
local causal interactions and iterating these effects in real time. They "simulate" themselves, in a trivial sense.
p.183 The problem of emergence arises out of attempting to make sense of the apparent macro/micro layers
in the natural world. I have argued that what I call weak emergence substantially solves this problem.
p.211 The recent bloom in the scientific study of complex systems is partly a result of advances in the
capability of inexpensive computers. Most scientific explanations of emergent behavior in Part II take the form of individual-
or agent-based computer systems... [Thomas] Shelling's model [JLJ - from chapter 12] shows how derivative social
structures can emerge out of the interaction of many elementary personal preferences of many individual people... social patterns
involving a person could be merely the unplanned and unanticipated result of aggregating that person's own local individual
preferences with those of many other people.
p.250 In describing a complex system we often find it convenient to introduce new theoretical terms...
for quantities that are not directly observable but are defined by relations among the observables.
p.251 Feedback control shows how a system can work towards goals and adapt to a changing environment...
What is required is ability to recognize the goal, to detect differences between the current situation and the goal,
and actions that can reduce such differences: precisely the capabilities embodied in a system like the General Problem
Solver.
