2001 Graduate Workshop in Computational Economics
Each student began a research project during the two-week
workshop. Below are brief descriptions of these various projects.
These projects will form the basis for dissertation chapters and/or
SIMS, UC Berkeley
Alessandro is studying how shared knowledge influences production of
complex goods. Such goods are ubiquitous in computational systems,
where the interacting knowledge of creators, mediated through
computers and communication networks, creates new goods. Alessandro
uses an NK-landscape to model the system. Each agent faces a binary
search problem, the solution of which depends both upon the agent's
choices and the choices of the other agents. As the network grows the
agents are able to better incorporate the activities of the other
agents in their search. He finds that network effects can
dramatically alter performance and the effectiveness of various
UC Santa Barbara
Keyvan is exploring the performance of trading agents in multiple
markets. The agents are drawn from the current literature in
economics, including variants of informed and uninformed traders, and
their actions are synthesized by a Bayesian market specialist. Over
time, more successful agents are increased via a replicator dynamic.
He finds that the dynamics of the model can lead to dramatic changes
in the price as destructive feedback loops form when the informed agents over
react to price signals and agglomerate on particular markets.
Chalmers University of Technology
Karin is looking at buyer and seller behavior in auctions of bundled
goods. Her initial work focuses on the study of dynamics in an
auction with a single seller and adaptive buyers. This work is then
extended to an auction in which the seller analyzes all of the
incoming bids to better identify and exploit the latent demand of
buyers. She finds that buyers can learn to productively bid in the
simple version of the game, though the ability to do so is closely
tied to the learning mechanism. The work is currently being extended
to the full coevolutionary model.
University of Michigan
Chris is looking at niche formation in information economies. In the
model producers attempt to attract consumers by offering different
bundles of information goods. Consumers pick the best bundle from
those offered by the producers, based on their valuations of each
bundle's attributes tempered by the ``clutter cost'' of having to read
things that are not of interest. Producers use a genetic algorithm to
search for profitable bundles. He finds that periods of niche
consolidation by the producers alternate with periods where one
producer or the other dominates. If producers are allowed to
coordinate their searches, they can both achieve higher profits as
long as the coordination is limited. Moreover, small increases in
clutter cost improve the ability of firms to make higher profits.
University of Massachusetts at Amherst
Jung-Kyoo is analyzing the evolution of cooperation in N-person social
dilemmas. Agents are assigned into groups and play a repeated
N-person social dilemma. Agents either interact with a random group
(global) or the same group (local). A genetic algorithm is used to
adapt the strategies with a selection mechanism that involves either
global or local agents. With random groupings, defection is the norm
with some occasional, short-lived outbreaks of cooperation (these
outbreaks are enhanced when selection is local). When agents stay
within the same group cooperative outcomes are much more likely, with
relatively high levels of sustained cooperation in many of the
resulting groups when selection is global, but not when it is local.
Universitat Autonoma de Barcelona
Ivanna is investigating the dynamics of a two-sided adaptive model of
buyers and sellers. In the model, coffee sellers decide on what
quality of coffee to offer customers based on attempts to adapt
policies that lead to higher profits. Buyers have aspirations for
coffee quality that adjust based on recent experience, and they search
for shops that can meet these expectations. She finds that the
willingness of agents to adjust their aspirations to recent
consumption has a strong influence on the system's dynamics. When
agents adjust aspirations slowly a monopoly forms in the industry.
Markets composed of heterogeneous agents result in a single,
high-quality firm that shares the market with many, less-profitable
competitors. When aspirations are rapidly adjusted a relatively
stable market composed of numerous firms ensues.
University of Chicago
Michael considers how learning impacts the development of public
policy. The model allows ``states'' that must make a binary policy
choice to emulate the choices of other states. Using the model he is
developing hypotheses about how policy salience, emulation, and
uncertainty interact to produce innovative policies. He is extending
the model by incorporating more elaborate learning structures and the
use of existing data sets to empirically ground the model.
California Institute of Technology
Maggie is analyzing city formation. Citizens have preferences over
both a private and a public good. Demand for the public good depends
on the tax share that the individual must pay, and thus it is linked
to the composition of citizens within a given jurisdiction. During
each round of the model a new jurisdictional split is proposed and if
a majority of the citizens approve the split occurs. Individual
citizens are allowed to move if they can find another citizen with
whom to swap locations. She finds that the number of cities rises as
the square root of the number of agents. She also notes that
heterogeneous preferences do not result in dramatically different
cities and that the social benefits of new city formation appear to be
quite limited in the current model.
Alex is modeling the formation of networks among heterogeneous,
game-playing agents. Agents playing a Prisoner's Dilemma game
``grow'' a network of partners with whom to play. Agents use a
generalized version of the Tit-For-Tat strategy to play the game
within their existing network. Networks evolve as agents, depending
on type, either make new connections or incorporate new partners from
the sidelines. Similarly, network connections are severed with
uncooperative partners. Such partners are returned to the sidelines
if they become completely isolated. He finds that inherently stable
networks can form in the system and he is currently exploring key
hypotheses about the dynamics of the system.
Riti is trying to understand the dynamics of bank runs and contagion.
Both informed and uninformed agents deposit money at multiple banks.
Agents withdraw their deposits either when they they need it for
private purposes or when they lack confidence in the bank's ability to
survive. She finds that certain parameters, such as bank size
differences and reserve requirements, can dramatically alter the
potential for bank runs and contagion. Based on the model, she is
exploring key policy variables that might enhance the stability of
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