Setting the Stage: Complex Systems, Emergence and Evolution
5
the point at which system starts exhibiting chaotic behavior, or the point
at which it becomes extremely sensitive to initial conditions. This sensitivity
sometimes produces bifurcations (or branches into two possible behaviors)
that are difficult to predict (Figure 1.3).
FIGURE 1.3: Bifurcation diagram in a logistic map. Adapted from [122].
1.3 Constructing Artificial Systems
Complex systems can be seen as large problems that can be solved as
collections of smaller problems. For instance, ant colonies and individual ant
behavior are being studied to give possible solutions to computer networking
problems [170], or understanding how prices behave in stock markets.
Large engineering applications, also made up of tiny parts working together, can have precise predictable behavior. These individual units always
perform as they ought to, unless they fail due to some dependencies which were
difficult to predict. Economic systems also exhibit a wide variety of emergent
behaviors, with humans sometimes not paying their credit bills regularly or
buying houses without paying mortgages, cited as some of the reasons for
2008 credit crunch [33]. This unpredictability and randomness of individuals, leads to the failure of large systems performing as predicted. The extent
of failure, having a domino effect on surrounding elements, depends on how
many individuals deviated, allowing complex systems research to become a
multi-dimensional problem with techniques from psychology and behavioral
economics, enhanced by methods in computer science.
5
the point at which system starts exhibiting chaotic behavior, or the point
at which it becomes extremely sensitive to initial conditions. This sensitivity
sometimes produces bifurcations (or branches into two possible behaviors)
that are difficult to predict (Figure 1.3).
FIGURE 1.3: Bifurcation diagram in a logistic map. Adapted from [122].
1.3 Constructing Artificial Systems
Complex systems can be seen as large problems that can be solved as
collections of smaller problems. For instance, ant colonies and individual ant
behavior are being studied to give possible solutions to computer networking
problems [170], or understanding how prices behave in stock markets.
Large engineering applications, also made up of tiny parts working together, can have precise predictable behavior. These individual units always
perform as they ought to, unless they fail due to some dependencies which were
difficult to predict. Economic systems also exhibit a wide variety of emergent
behaviors, with humans sometimes not paying their credit bills regularly or
buying houses without paying mortgages, cited as some of the reasons for
2008 credit crunch [33]. This unpredictability and randomness of individuals, leads to the failure of large systems performing as predicted. The extent
of failure, having a domino effect on surrounding elements, depends on how
many individuals deviated, allowing complex systems research to become a
multi-dimensional problem with techniques from psychology and behavioral
economics, enhanced by methods in computer science.