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Ant Colony and Market Intelligence

 


"One lesson western thought has had to learn slowly in modern times is that if we try hard enough to reduce anything to pure logic..........such attempts founder. The world can not be reduced to pure logic and caged within it. Sooner or later it slips out to reveal its true messiness, and all such projects fail."

-W. Brian Arthur

 

Ant Colony:

Social insects (ants, bees, social wasps etc.) take large territorial possession displacing solitary insects (cockroaches, grasshoppers, beetles etc.) from the most favored nest sites and defensible foraging ranges. Social insects like ants possess such environmental dominance because they act as superorganism where heterogeneous agents (with different tasks at hand) engage in cooperative group behavior. The order in which the ant colony operates, it looks like a functional whole. But nothing in the brain of a worker ant represents a blue print of the social order. The self organizing nature of the colony makes the distributed colony intelligence greater than the sum of intelligence of all the members.

Ant colony as complex adaptive system has three distinct features:

  • The system consists of a number of heterogeneous agents making decisions about how to behave which evolve over time
  • Agents interact with one another
  • In the process of emergence, whole becomes greater than the sum of the part
 

Market Intelligence:

During mid-1980s Brian Arthur along with some other contemporary economists was looking at new economic perspective that would stand in the opposite direction of the then established economic theory of perfect rationality, equilibrium, diminishing returns and of independent agents always facing well-defined problems. Behavioral rationality, nonequilibrium, increasing returns and interconnected agents facing fundamental uncertainty in problems of decision making seemed to be the economic reality that most economists ignored. Brian Arthur coined it as complexity economics that isn't machine-like and can not be reduced to simple equations.

Later Brian Arthur attempted to design a primitive artificial economy that would execute on his computer. The idea was to simulate full development of an economy. He found it difficult to execute and resorted to much simpler and more feasible way to test the complexity nature of the economy. He would simulate a stock market where few computerized investors would buy and sell stock, try to spot trends, and even speculate and in the process would learn to get smart with each random condition or rule applied that would be available in the simulation.

At first, Investors would choose different methods randomly to execute buy and sell decision and later would adjust or replace them with new ones depending on success or failure. This allowed the investors to keep adjusting and discovering. When looked closely, Brian Arthur noticed emergence of real market phenomena in the simulation: small bubbles and crashes, periods of high volatility followed by periods of quiescence and correlations in prices and volume. This insight was something that standard economics based on identical agents using rational expectations could not show. Economy as a complex adaptive system represented reality.

Aligning with this new economic thinking, Santa Fe group pointed out four distinct features about the economy or market that include:

  • Dispersed interaction
  • No global controller
  • Continual adaptation
  • Out of equilibrium dynamics

Depending on the interaction between the market participants, the collective intelligence can be greater than the sum of all the market participants' intelligence. But with changing dynamics of the market (e.g. new products, new concepts, new behavior), the system adapts and evolves and in the process the market learns what doesn't work and what can work. Bubble happens, crashes take place and the agents learn or relearn the new or old economic reality.

 

 

 

 Sources:

  • Complexity and the Economy by Brian Arthur
  • Investing: The Last Liberal Art by Robert G. Hagstrom
  • The Superorganism by Bert Holldobler and E.O. Wilson
  • Embracing Complexity by Tim Sullivan

 

 


 

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