Game Development Reference
In-Depth Information
Categorizing emergence
Scientists distinguish among various levels of emergence in a complex system. Some
effects are more emergent than others. Feedback loops and the different scales that
exist within a complex system together go a long way to describe and explain dif-
ferent levels of emergence. In his paper “Types and Forms of Emergence,” scientist
Jochen Fromm uses feedback and scales to build the following taxonomy of emer-
gence (2005).
In the simplest form,
nominal
or
intentional emergence
, there is either no feedback or
feedback only between agents on the same level of organization. Examples of such
systems include most man-made machinery where the function of the machine is
an intentional (and designed) emergent property of its components. The behavior
of machines that exhibit intentional emergence is deterministic and predictable but
lacks flexibility or adaptability. A speed governor and a thermostat are examples of
this type of predictable feedback.
Fromm's second type of emergence,
weak emergence
, introduces top-down feedback
between different levels within the system. He uses flocking to illustrate this type of
behavior. A bird reacts to the vicinity of other birds (agent-to-agent feedback) and at
the same time perceives the flock as a group (group-to-agent feedback). The entire
flock constitutes a different scale from the individual birds. A bird perceives and
reacts to both. This behavior is not confined to birds; schools of fish behave simi-
larly. Flocking can be generalized to any kind of unit capable of perceiving both its
immediate surroundings and the state of its group as a whole.
One step up the complexity ladder from weakly emergent systems are systems that
exhibit
multiple emergence
. In these systems, multiple feedback traverses the different
levels of organization. Fromm illustrates this category by explaining how interest-
ing emergence can be found in systems that have short-range positive feedback
and long-range negative feedback. The stock market exhibits such behavior. When
stocks are going up, people begin to notice and to buy more, driving the price up
further (short-term positive feedback). People also know from experience that the
stock will eventually reach a peak, and they make plans to sell the stock when they
believe it has reached its peak, thus driving the price down (long-term negative feed-
back). The phenomenon works in reverse, too: People will sell a stock when they see
it dropping but buy later when they think it has reached bottom and is a bargain.
John Conway's Game of Life also exhibits this type of emergence. The Game of Life
includes both positive feedback (the rule that governs the birth of cells) and nega-
tive feedback (the rules that govern the death of cells). The Game of Life also shows
different scales of organization: At the lowest end there is the scale of the individual
cells; on a higher level of organization, you can recognize persistent patterns and
behaviors such as gliders and glider guns.
