Social
Science Computer Models
[Case
Studies, Tutorial Examples]
[Ongoing Projects]
[Experiments in Stigmergy]
This page gives a very quick overview of the computer models
developed and under development at Agent-lab.
The detailed descriptions of these models can be found elsewhere
on the web or in printed form. We have an incentive to make
them all available on the World Wide Web in electronic form,
but till that time, please contact us directly in case of any
difficulties.
Case
Studies, Tutorial Examples
These models were
developed mostly for educational purposes and serve as examples
in our modeling courses. They are replications of previously
published models. As these original models are usually not individual
(or agen) based ones, the replication also meant the redesign
of the subject model. The transformation of an ordinary model
into an agent based one is a pretty interesting and up to now
not well studied problem, so these experiences also gave us
very important insights into the fundamentals of agent based
modeling, and modeling in general. Some of these models also
served as case studies for the development of our
modeling environment.
Introductiory
Experiments with Logistic Lattice Maps
| These
were the first experiments carried out in the Systems
Laboratory. They were used to design the fundamentals
of our
modeling environment.
Click on
the thumbnail on the rigth to see the full picture.
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Replication of
Paul Krugman's Edge City Model
| This
minimal model of self-organization of urban places was
published as a demonstration in Paul Krugman's
book on The Self-Organizing Economy. As the original
model wasn't really agent-based, we reimplemented it
using this novel approach. This project gave us very
deep insights into the hidden assumptions of the original
model, and into the problems which occur when the way
of thinking shifts from top-down to botton-up, which
is one of the main challenges of agent (or individual)
based modeling and simulation.
The transformation
project resulted in various results, one of the most
important of which is a case study we' ve developed.
We use this material in our education to give insights
into the fundamentals of this novel approach in modeling.
The final version of the replicated model also serves
as an example of our MAML
language.
The details
of this project are discussed elsewhere.
On the
right a series of pictures are presented showing the
process as central places evolve. (Click on the thumbnails
to get the full pictures.) For more explanations and
more results, please refer to the separate page mentioned
above.
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Replication of
Thomas
Schelling's Segregation Model
| This
fairly simple but excellent piece of work is somewhere
in the roots of social science computer simulations.
Moreover, although it was developed decades ago, it
fits pretty well into the concept of agent based modeling.
Thanks
to its simplicity this model can be used as an introductory
example at our Social Science Simulations course,
and as a programming example of our MAML
language.
|
These are screen captures of the simulation.
Click on the thumbnails to get the full pictures.
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Ongoing
Projects
The following models
are under development, so only a limited set of results is available.
In this section we give a short overview of each projects including
as much illustration as we can without taking serious resources
from the real development. The results of these projects will
appear on-line as soon as possible.
Dynamical Economy:
The Case Of Inflation (UNDER
DEVELOPMENT)
| This
project is the last one in the series of our studies
examining the transition from traditionally implemented
models into agent based ones. The replication will serve
as an example of the
modeling environment we have developed. The model
may also be subject of further improvements and studies.
The original
model was written by Perazzo, Reich,
Schvarzer, and Virasoro, and was published
in Complexity,
col 2, No 6, 1997.
|
A Simple Economy
Model (UNDER DEVELOPMENT)
| This
project is aiming at the replication and further development
of Alex Viskovatoff's Model of Simple Economy. |
The Senegal Model:
A Modified Version (UNDER DEVELOPMENT)
| This
projects is about modeling a country's (let's say Senegal's)
population, economy and politics (to some extent). It
was highly inspired by Peter Allen's work on
modeling Senegal. |
A Model of Fast
Food Restaurant Chains (UNDER
DEVELOPMENT)
| In
this model of urban development different strategies
of unit location for competing fast food restaurant
chains are explored based on real GIS data of Budapest.
On the
right and below a couple of pictures are presented
illustrating the kind of work we are doing. (Click
on the thumbnails the get the full pictures!)
|
The
roadmap of Budapest showing the means how different
locations in the town can be accessed. Three reastaurant
units (of different chains) are also indicated.
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 The
cost their consumers need to spend on travelling,
calculated by two different restaurant units, based
on the roadmap above.
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 The influence of the indicated restaurant
units on costumers. |
A Simple Model
of Common Decision (UNDER DEVELOPMENT)
| The
main objective of this project is to give another example
of building models in MAML.
However, it also tries to capture some interesting behaviour
of human societies, namely the process of making common
decisions effecting the community. In the future this
oversimplified model might be subject of further development. |
Experiments
in Stigmergy
The concept of stigmergy
was introduced by a French biologist, P.P. Grassé
in the '50s when he was studying the behaviour of social insects.
The word itself comes from two Greek words: stigma (outstanding
sign), and ergon (work) giving the meaning incentive
to work by the product of work itself. The concept vaguely
is a coordination mechanism, which allows fairly simple aminals
to achieve highly ordered emergent behavior at the level of
the society, composed of simple activities through indirect
communication. One of the most exciting things about stigmergy
is that it leads to pretty robust emergent phenomena, which
remain virtually unchanged under heavily changing circumstances.
The concept gained
new acceptance in the field of Artificial Life in the '90s,
and in Computer Sciences very recently. Although the origins
of stigmergy are pretty much connected to social activity
and behaviour, little if any work were devoted to study the
mechanism in the context of human societies, while it seems
to be a natural concept to describe some phenomena in our
everyday life. Think of the way how culture (e.g. litterature
or science) evolves: to some extent this common product of
human kind can be seen as a product of loosely coordinated
activities of millions of agents, each of them being inspired
by the perceived parts of the common product (the product
of the others). Or think of the self-organizing structure
of the Internet, especially how new techniques, standards
and concepts spread. These all could be modeled under the
general concept of stigmergy.
If you are interested
in some interesting ideas of Mitchel
Resnick on the decentralized world around us and our centralized
mindset, follow
this link.
Deneubourg's
Path Planning Ants
| This
model is a famous one, often cited in the context of
stigmergy. It nicely demonstrates that individuals in
a society can produce highly coordinated behavior at
the level of the society, even if they are not aware
of themselves doing that.
The model
captures the ants food seeking behaviour. Ants are
wandering around in the space looking for food while
leaving trails of pheromone (chemical sign)
behind. They tend to follow beacon trails left
by homing ants carrying food. When they eventually
find the food source, they try to get home by tending
to follow the pheromone path and leaving beacon
trail behind. The pheromone and the beacon
evaporates over time.
This model
was developed in part to study the technical details
needed to develop our
simulation environment, but it was also very useful
in understanding the concept of stigmergy.
On the
right there is a series of screenshots presented from
one typical run of the simulation. (Click on the thumbnails
to get the full pictures!) The food source is represented
by the blue dots in the upper left corner of the space.
The nest is in the middle of the grid, denoted by
a yellow dot (which is often hidden by the ants).
Ants looking for food are the white, while ants carrying
food are the green dots on the screen. The screeanshots
are divided into too parts, one of them showing the
concentrate of pheromone, another showing that
of the baecon.
The series
shows as the ants start out from the nest (Figure
1), wander around (Figure 2), begin to build the trail
(Figure 3 and 4), and tend to stabilize the trail
and remain on it. Note however, that this run was
not perfect in the sense that a number of ants remained
off the path built by the others.
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Figure
1
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Figure
2
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Figure
3
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Figure
4
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Figure
5
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Bonabeau's Model
on Cemetery Organization in Ant Societies
| This
is one of the core models of the concept of stigmergy,
and in broader sense that of decentralized self-organizing
systems. It is fairly similar to Deneubourg's Model
of Breed Sorting Ants.
In
this model agents acting upon local information (from
their environment) collect entities (breed or dead
bodies) initially scattered around the space into
clusters, without any explicit coordination or communication
amongst each other
The
model was used to gain deeper understanding of the
concept and also to study the underlying coordination
behavior. The illustrations to the right come from
a slightly modified version of the original algorithm,
which was developed as an example of our MAML
language. Please find the detailed description
there.
|
Click
on the thumbnails to get the full pictures!
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Uniformization
of Local Culture (UNDER DEVELOPMENT)
| This
model was inspired by Deneubourg's Breed Sorting Ant
Society Model and tries to capture the process how different
cultures carried by moving agents tend to result in
spots with uniform local culture.
The model
is still being developed, but some screenshots are
available on the right to illustrate it. The green
and white dots are the agents wandering around, while
the red dots represent the level of uniformness of
the culture at the given location. The brighter the
red is, the more uniform the local culture became.
Click
on the thumbnails for the full pictures!
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