Emergence 2006
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The field of emergence is "emergent" on two separate levels. In the literal sense, emergence is the process by which simple agents, adhering to a simple rule-set, coalesce into complex systems. In and of itself, the actual study of emergence also exhibits emergent characteristics, as demonstrated in Steven Johnson's Emergence: The Connected Lives of Ants, Brains, Cities, and Software. Johnson manages to provide the reader with a primer on how the emergent train of thought can be applied to numerous seemingly disparate subjects. What soon becomes evident in Johnson's broad discourse is that, albeit software development, the study of city and socioeconomic structure, neurology, and myrmecology—the study of ants—to name a few, an emergent point of view proves to be an effective tool in studying these complex, and often times chaotic, systems. By providing both the historical motivations for studying emergence, and through the firsthand accounts of those at the forefront of emergence in each of the aforementioned fields, Johnson delivers substantial evidence that agents on a low level have the ability to self-organize and exhibit macroscopic behavior through feedback networks and adaptation. It is due to this rather ubiquitous nature of emergent tendencies that a colony of ants, for example, may be able to provide more insight into the lives of humans than meets the eye.

Ant colonies have been known to be highly organized and efficient in nearly every facet. Upon initial inspection, it appears as though these colonies materialize through a top-down hierarchal construction. The societal structures in which humans live are products of a top-down hierarchal system. Local and federal governments are appointed by the individuals in a society and these leaders subsequently impose the laws by which the society must abide. Since the very world in which people live is engrossed by a centralized state, it is only natural to assume that the same applies to ant colonies. Through his dialogue and interaction with Deborah Gordon, a renowned behavioral ecologist, Johnson presents the reader with intriguing facts about the delegation of work amongst ants in a colony.

Contrary to naďve belief, the queen does not dictate each individual ant in the colony—bearing the size of the ant population in the colony, it is evident that such a task would be unfeasible for a single queen ant to undertake. This lack of leadership does not imply that anarchy reigns supreme in the colony. Rather, Johnson presents the notion of an ant colony as an archetypal example of bottom-up organization. Much in the same way that slime mold cells release cyclic AMP as to assemble other cells—which, in turn, "triggers waves of cyclic AMP that wash throughout the community"(Johnson 14)—ants rely heavily upon pheromone trails left by other ants. The presence of a pheromone trail may indicate to an ant that a fellow worker has found a luscious cornucopia of food; because of this feedback, the said ant will follow the path to the food and similarly leave a pheromone trail for more ants to follow. In this sense, the individual ants are not independently scouring for food throughout the entire day. Although they do act independent from one another at first, the ants eventually converge into a single, coherent being. What is even more startling about the emergent behavior of the ants is that the paths they create often times are geometrically optimal. On describing one of the colonies she has been studying, Gordon states "they've built the cemetery at exactly the point that's furthest away from the colony. And the midden (waste) is even more interesting: they've put it at precisely the point that maximizes its distance from both the colony and the cemetery" (Johnson 33). Similar to the way biological evolution motivated John Holland and Danny Hillis to develop genetic algorithms and genetic programming, respectively, the uncanny potential of pheromone trails was used to attack a daunting conundrum in mathematics—the traveling salesman problem.

Marco Dorigo, an artificial intelligence researcher at the Free University of Brussels, exploited the pheromone schema in an attempt to map out the shortest path between 15 different cities. Dorigo essentially sent out a swarm of individual virtual salesmen, all of whom would explore the various ways of visiting each of the cities. When a solution was found, the agent would retrace its path and leave a pheromone trail for the other agents to follow. After several generations of salesmen scouring the map, following thick pheromone paths, and retracing efficient paths, an optimal solution eventually emerges. Johnson furthers the idea that close interaction between agents in a system has implications on a larger scale. In fact, Johnson believes that it is in the best interest of neighborhoods to interact in order to materialize into a vibrant city.

In situations where neighborhoods are secluded from one another, the only things that "emerge" are xenophobia and an overall lack of emergence. In cities where neighborhoods are both adjacent and within walking distance of one another, the individuals in the city will most likely communicate when they cross paths on a sidewalk. The local interaction between the different groups is crucial if the groups are to eventually emerge. Although such emergence may not be immediate, such coalescence may come to fruition on longer timescales. Thus, given enough interaction and social feedback, a united city working as one can form from a set of disjoint groups.

Johnson stresses that although emergence seems almost applicable in every situation, there are certain conditions that must be met in order for there to be emergence in the first place. One of his most interesting arguments is that the vital communication must be between agents working on the same level. Emergence is virtually nonexistent when agents from different scopes attempt to interact. Johnson gives a compelling argument with cars in a city. A car which travels on a stretch of highway does not provide feedback to the neighborhoods it passes—cars and neighborhoods are on different scales. Rather, the car will provide feedback for the other cars zipping down the highway, and visa versa. The feedback on this level and in this scenario leads to the emergence of traffic jams.

Despite the fact that traffic jams emerge from the feedback between cars, Johnson suggests that feedback could also be used to combat such predicaments. By implementing a feedback network between cars and stoplights, it is possible that a homeostatic timing scheme could be derived which would optimize the movement of the cars such that jamming would be minimized.

The recurrent thread that seems to resonate all throughout Johnson's work is the reliance that emergent systems have on feedback. Individual agents are able to converge and attain macroscopic homeostasis through interaction with similar agents in the microscopic scale. The fact that emergence is exhibited on so many unique levels is a testament to how powerful it is. Johnson does a marvelous job by lucidly presenting this budding idea and demonstrating how far-reaching its implications are. Notwithstanding Johnson's vast array of emergent examples, it is truly a grave underestimate to believe that study of emergence has reached its pinnacle. Emergence has opened the eyes of those who have studied it and has inspired fascinating work in a large number of circles. For many, mankind's current understanding of emergence of merely a scratch on the surface of something bigger. Regardless of whether emergence holds the key to true artificial intelligence, or if the field itself emerges into the highly coveted 'Theory of Everything', it is wise for researchers and enthusiasts alike to continue pushing the limits of emergence.