[MUD-Dev] Sugarscape: A-Life variation with economic interests

J C Lawrence claw at under.engr.sgi.com
Tue Jun 30 15:27:51 New Zealand Standard Time 1998


Consider this from the viewpoint of the various resource economies
we've discussed here for such as mobile populations, money supply,
population movement, player chararacter and NPC careers, etc.

It also bears a close relation to the sharks game and other similar
simulations discussed here.

Supporting URLS:

  URL:http://www.glue.umd.edu/~badger/sugarscape/
  URL:http://www.brook.edu/SUGARSCAPE/  (where it all started)


URL:http://www.sciencenews.org/sn_arch/11_23_96/bob1.htm

November 23, 1996


The Gods of Sugarscape

Digital sex, migration, trade, and war on the social science frontier

By IVARS PETERSON 

In the ritualized warfare of the game of chess, the board is a
miniature battlefield on which opposing commanders-in-chief marshal
their forces.

Each playing piece has a particular pattern of allowed movements, and
the game's rules shape the battle. The combatants can try out
different strategies, directing bold attacks, mounting stubborn
defenses, or waging wars of attrition across the grid.

At the Brookings Institution in Washington, D.C., social scientist
Joshua M. Epstein and computer modeler Robert Axtell also have a
playing field on which to audition their ideas.  They play their game
on a 50 by 50 square lattice on a computer screen, and the playing
pieces, or agents, are colored dots occupying some fraction of the
squares.

Epstein and Axtell are actually more like gods than commanders. They
define the landscape, set the rules, and characterize the
agents. Instead of participating in the action, they step back to
observe what happens as the swarming agents, left on their own in
these simulations, move about, gather sustenance, reproduce, and die
off according to their programmed predilections.

>From the patterns that emerge, the re-searchers can glean insights
into human social and economic behavior. "We grow social
structures--artificial societies--in the computer," Epstein says. "We
can examine population growth and migration, famine, epidemics,
economic development, trade, conflict, and other social issues."

"It's intellectually provocative work," comments economist Sidney
G. Winter of the Wharton School of the University of Pennsylvania in
Philadelphia. The resulting simulations "provide challenges to
existing treatments of social and economic matters."

Epstein and Axtell describe their project in the newly published book
Growing Artificial Societies: Social Science from the Bottom Up
(Washington, D.C.: Brookings Institution/MIT Press).

"It's a magnificent achievement," says John L. Casti of the Santa Fe
Institute in New Mexico. "What they've done in building a world inside
a computer is a glimpse of how ...science will be done in the 21st
century."



The cyberworld in which Epstein and Axtell's agents dwell is known as
Sugarscape. It's a two-dimensional landscape, represented as a square
grid, containing two regions rich in a renewable resource arbitrarily
called sugar. Every agent is born into this world with a metabolism
demanding sugar, and each has a number of other attributes, such as
visual range for food detection, that vary across the population.

They move from square to square according to a simple rule: Look
around as far as your vision permits, find the unoccupied spot with
the most sugar, go there, and eat the sugar. As it is consumed, the
sugar grows back at a predetermined rate.

An agent's range is set by how far it can see. Every time an agent
moves, it burns an amount of sugar determined by its given metabolic
rate. Agents die when they fail to gather enough sugar to fuel their
activities.

With hundreds of agents roaming the landscape, "interesting things
begin to happen," Axtell says.

Initially distributed at random across the landscape, the agents
quickly gravitate toward the two sugar mountains. A few individuals
end up accumulating large stocks of sugar, building up a great deal of
personal wealth. These happen to be agents that have superior vision
and a low metabolic rate and have lived a long time.

A few others, combining short vision with a low metabolic rate, manage
to subsist at the fringes, gathering just enough to survive in the
sugar badlands but not looking far enough to see the much larger sugar
stocks available just beyond the horizon.

At its simplest level, the Sugarscape model represents a kind of
hunter-gatherer society, Axtell explains.

Yet even this rudimentary model reproduces the kind of strongly skewed
distribution of wealth generally observed in human societies--where a
few individuals hold most of the wealth and the bulk of the population
lives in relative poverty.


Introducing sex and reproduction to Sugarscape is as simple as adding
to the agent's string of numbers a few bits specifying gender.

A rule specifies the allowed behavior: An agent must select a
neighboring agent at random.  If the neighbor is of the opposite sex
and of reproductive age, and if one of the two agents has an empty
neighboring site (to hold offspring), a child is born. The child
inherits a mixture of its parents' genetic attributes.

This new dimension enables the researchers to investigate the effect
of cultural forces on biological evolution and vice versa. For
example, in the absence of any cultural factor, agents with relatively
low metabolism and high vision enjoy a selective advantage in
Sugarscape.

Now, suppose that when an agent dies, it can pass on its accumulated
holdings of sugar to its offspring. How does this cultural convention
influence evolution?

The Sugarscape model suggests that agents who might otherwise have
been "weeded out" are given an extra advantage through inheritance,
Epstein says. The average vision of the population doesn't increase to
the same high level eventually reached in a population where no wealth
is passed on.

The researchers can also modify their model to observe the emergence
of tribes (identified by numerical tags) and the process of
assimilation (changing affiliation to join the local
majority). Inevitably, there arises a primitive kind of combat, in
which agents of two different tribes may plunder each other for sugar.

Various combat rules lead to patterns of movement that differ from
those produced by the standard "eat all you can find" rule. For
example, some combat rules lead quickly to strictly segregated
colonies, each clinging to its own sugar peak. In other cases, one
side wipes the other out.


The Sugarscape model also offers insights into other phenomena, such
as the introduction of trade. In this case, the landscape contains
heaps of two resources: sugar and spice. The agents are programmed
with different metabolic rates, or preferences, for each of the two
commodities. They die if either their sugar or their spice store falls
to zero.

A mathematical formula called a welfare function allows each agent to
compute how close it is to sugar or spice starvation. The agent then
strives to gather more of the commodity it needs.

An additional system of rules specifies how agents bargain for and
exchange sugar and spice according to their needs. These rules enable
the researchers to document how much trade transpires and at what
price exchanges occur.

When agents are allowed to live forever, so long as they never run out
of food, the sugar-spice model shows that the average trade price
converges to a stable level. Economic equilibrium emerges, Epstein
says, just as textbook market economics predicts.

However, when Epstein and Axtell make the agents "more human" by
giving them finite lives and permitting their preferences to evolve,
the price no longer stabilizes and the market never reaches
equilibrium.

"The assumption that we can let markets produce efficient allocations
[of capital or resources] on their own is deeply challenged by our
work," Epstein claims. "We see how brittle traditional economic theory
really is."


Epstein and Axtell's Sugarscape simulation is just one example of a
wide variety of computer models now being developed on the basis of
interactions between agents governed by given rules rather than on
equations defining global behavior. The idea is to model from the
bottom up--seeing behavior emerge out of interactions among
individuals--instead of from the top down--deriving the behavior of
individuals from overarching laws.

Researchers at the Santa Fe Institute, Los Alamos (N.M.) National
Laboratory, and elsewhere have worked out agent-based models of urban
transportation systems, insect colonies, business organizations,
financial markets, and other situations. Such approaches are also
useful in studies of artificial life--forms that exist only in the
computer yet mimic certain aspects of the behavior of living organisms
(SN: 8/10/91, p. 88).

What distinguishes the Sugarscape project is its emphasis on seeing
what sorts of socially relevant behavior can emerge from the
collective interaction of individuals following the simplest possible
rules. "The surprise is that we can grow [complex, recognizable
behavior] with incredibly simple rules and simple agents," Epstein
says.

Such agent-based modeling shows that social norms can arise out of
very primitive behavior, though it doesn't necessarily demonstrate how
the norms actually came about, notes economist Thomas Schelling of the
University of Maryland in College Park.

Epstein insists that although these bare-bones models can't really be
used to make specific predictions, they can suggest explanations of
some widely observed macroscopic phenomena, from distributions of
wealth in typical societies to erratic price fluctuations in markets.

"We think of our model as a laboratory for social science," Epstein
says. Researchers from a wide variety of disciplines, including
economics, biology, demographics, and environmental studies, can use
this approach as a research tool to tackle oft-neglected,
cross-disciplinary issues like the effects of inheritance on the
genetic evolution of a system.

"One can readily imagine hypotheses or mechanisms that no one has
thought of before arising out of this kind of model," Winter adds.

Like others working with agent-based models, Epstein and Axtell must
interpret the patterns they observe on the computer screen. After all,
their agents are no more than strings of digits and the observed
behaviors no more than patterns in a computer's memory.

"It is the act of interpretation . . . that allows these electronic
worlds to make contact with their real-world counterparts," Casti
notes.

In the case of Sugarscape, the model is more a metaphor than a
realistic depiction of society.  No one literally spends a working day
accumulating sugar. The landscape and agent characteristics are simple
stand-ins for the more complicated things that occur in the real
world.

In one application of their method, Epstein and Axtell are now working
with archaeologist George J. Gumerman of Southern Illinois University
in Carbondale and his colleagues to "grow" the Anasazi society, a
Native American culture that flourished in the U.S. Southwest for
hundreds of years, then suddenly disappeared. The archaeologists have
data on weather patterns, crop yields, and other environmental
conditions during that period, along with information about the
Anasazi culture.

"This gives our modeling an empirical target," Epstein says. The
researchers hope that agent-based simulations may shed light on
whether environmental or cultural factors were primarily responsible
for the society's abrupt decline.

Epstein and Axtell are also working with H. Peyton Young of Johns
Hopkins University in Baltimore to study how caste systems, in which a
small elite demands more than its fair share, arise in societies
(Formulas for Fairness, SN: 5/4/96, p. 284). "We want to know whether
or not equity comes about naturally in social systems," Young says.

The Sugarscape laboratory is still very much in the development
stage. Re-searchers are just starting to examine ways of tailoring
this approach to address specific needs and issues in the social
sciences, economics, and elsewhere.

One key issue in the Sugarscape approach involves how to tweak the
model to obtain such phenomena as the emergence of governments. "There
may be some kind of threshold beyond which you can't take a step up in
understanding . . . human organization without making the agents
smarter," Winter says. "The problem is how to make the agents smarter
in a way that remains true to the basic approach."

Sugarscape is already an immensely attractive playing field because
the limited repertoire of the agents makes it easy to understand,
measure, and depict what's going on and why the agents behave as they
do. Moreover, typical Sugarscape experiments take only a few minutes
on an ordinary personal computer.

"There are lots of opportunities to try things out," Epstein
says. "Our artificial societies let you get your teeth into things
that conventional theory can't handle."

The Sugarscape effort is part of Project 2050, a cooperative venture
of the Santa Fe Institute, the Brookings Institution, and the World
Resources Institute in Washington, D.C., to identify conditions for
sustainable development on a global scale.

By providing insights into population growth, resource use, migration,
economic development, conflict, and other global social processes,
games played on the Sugarscape grid may help shape the policies needed
to direct the future course of society.

--
J C Lawrence                               Internet: claw at null.net
(Contractor)                               Internet: coder at ibm.net
---------(*)                     Internet: claw at under.engr.sgi.com
...Honourary Member of Clan McFud -- Teamer's Avenging Monolith...




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