Evolution of Central Places (Urban Morphogenesis)
An agent-based replication of Paul Krugman's Edge City model.
A modified version of Eric Bonabeau's model of
Organization in Ant Societies.
This is one of the core models of the concept of stigmergy, and in
a 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), that were initially scattered around the space,
into clusters - without any explicit coordination or communication amongst
each other. The workl presented here is a slightly modified version of
the original model. The interesting phenomenon here is that while the algorithm
coded in the individual agents is fairly simple and involves no (direct)
communication with the others, the performance of the society results in
a fairly ordered landscape. Note that in the original model the ants obtain
no information at all from the global level, while in this version they
do use the initial density for decision making.
The algorithm performed by the individual agents is the following: they
wander around the space randomly, exhibiting Brownian motion. At each location
they decide if swapping the item they are carrying for the one at the given
location results in better local organization. (If they are carrying something
and there is nothing at the given location, then swapping means putting
the carried item down; while when they are carrying nothing but there is
some item at the location, swapping means picking the item up.)
Source Code for 1.0.2 and for 1.3 (and higher)
This is a simple simulation vaguely described in
This model describes cars moving forward in lanes. The cars slow down
if they see other cars ahead of them, and stop if they cannot move furhter.
On the other hand, if the way clears, they start to move again, increasing
their speed until it is possible (as long as there is no car ahead of them,
and they have not reached their maximum speed).
The interesting emerging behaviour to study here is that of the occurrence
of traffic jams, which move backward compared to the cars'
Source Code for 1.0.2 and
for 1.3 (or higher)
Dynamical Economy Model of Perazzo, Reich,
Schvarzer and Virasoro
This is an agent-based replication of a model, that appeared in Complexity,
vol 2, No 6, 1997.
(Written by the authors of the original Swarm implementation.)
Source Code for 1.0.2: (This simulation consists of several files. You
need all of them to be able to run it!)
for 1.3 in tar.gz format.
The previous code slightly modified to run with Swarm 1.4.1
in tar.gz format.
Adapted to Swarm 2.1.1
in tar.gz format.
Again a popular Swarm demo re-implemented in MAML.