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Herding Simulator - ver. 1.12 (11 Feb 2004)
The Herding Simulator is a simple tool written in VB6 that allows the
user to set up a network, and run simulations to analyse herd behaviour,
clustering and guru effects under different types of network topologies. The
program is based on Andreas Krause's model, outlined in [1]. More advanced
features such as Differential Memory and Dynamic Weights have been added to this
model.
To run simulations, first create a network, by selecting the appropriate
settings for network size & shape, and network type, and clicking the "Create
Network" button. Then, on the lower part of the window, select the price
function, and click on "Start Simulation". Once the simulation has finished, you
can analyze the degree distribution by going into the Tools menu, and selecting
Network Statistics.
What's new in version 1.11?
- Dynamic animaiton of star network formation
If you have the VB libraries already installed on your PC, you can run the
program by clicking on the link at the top of the page. Otherwise, you will need
to download
this setup, unzip the files in a temporary folder, and run the setup.exe.
The installation will create an icon under Start>Program Files>Herding
Simulations.
Feel free to email me any questions/bugs/suggestions to e-mail: aalent
(non-Essex users should add @essex.ac.uk to create full e-mail address)
Have fun with it!
Amadeo
Older versions
Version 1.10
-
Run version 1.10
- What's new in version 1.10?
- Added the calculation for "Herding
coefficient" under Network Statistics
Version 1.9
- Run version 1.9
- What's new in version 1.9?
- Fixed bug where links disappeared when setting the
Minimum Threshold setting to 0
- Fxed bug where the statistical calculations for the
theoretical values were incorrect When having the option of "Enforcing
self-inference" turned on.
Version 1.8 - 1.6
- Run version 1.8.
- Run version 1.7.
- Run version 1.6.
- What's new:
- Added a new pricing function "Random rewards with correlation"
- Added an option to "Enforce self-inference", that is, nodes cannot break
the link with themselves
- Modified the algorithm, so the weight of the self-inference link is the sum
of the outgoing links
Version 1.5
-
Run version 1.5.
- What's new:
- Added a minority price function
- Fixed problem with the calculation of clustering coefficient
- Added the theoretical values for a random graph with the "network
statistics"
Version 1.4
Version 1.3
-
Run version 1.3.
- What's new:
- Option of choosing Lattice/Toroid shape
- Fixed some bugs on the switching of links when using Dynamic Weights
- Added a scroll bar to play back the animation
- Added a Tools menu for exporting price and weights data to Excel
Version 1.2
-
Run version 1.2.
- What's new:
- Doesn't round up the price change when using the P(t) function. However,
the rewards are still given as +1 or -1
- Added an Animation feature, to dynamically see which nodes are "Buyers" and
which nodes are "Sellers"
- Clicking on a node allows the user to manually change the weights of the
links
- Dynamic weight adjustment
Version 1.1
-
Run version 1.1.
- What's new:
- More types of networks available
- Different pricing functions
- New graph to view Price movement
- Ability to Export data to MS Excel for further analysis
Version 1.0
To run the simulation without interaction between the nodes, and notice the
randomness of the network with no interaction, you can do any of the
following:
- Set M = 0 (if we don't use past experience, there will not be any
interactions)
- Set p = 0 (if there are no connections, no interaction)
- Use the option button for no interaction
[1] Krause, A. "Herding without Following the Herd: The Dynamics of
Case-based Decisions with Local Interactions", University of Bath
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