Farsi / Persian
NetLogo User Community Models
## WHAT IS IT?
Implementation of **The Naming Game** model mentioned in the paper:
> Baronchelli, A., Felici, M., Loreto, V., Caglioti, E., & Steels, L. (2006). Sharp transition towards shared vocabularies in multi-agent systems. Journal of Statistical Mechanics: Theory and Experiment, 2006(6), P06014–P06014. https://doi.org/10.1088/1742-5468/2006/06/p06014
This model is a way to study the evolution of words referring to an object in a closed world where a pair of people try to name an object by acting as a sender and reciever.
## HOW IT WORKS
1. The model starts with `num-agents` number of people. Each person in initialized with an empty list of words.
## HOW TO USE IT
SETUP button — sets up the model by creating the people.
The following inputs control how the model is setup:
SAMPLE-NEIGHBOR switch — weather to sample reciever from neighborhood of radius `neighbor-radius` of a sender
## THINGS TO NOTICE
Notice how the total unique words first rise to a max value and then converges to a very low value. If the `neighbor-radius` is very low then total unique words may converge to something small but not equal to 1. Also, notice that the mean number of words also rises
## THINGS TO TRY
* Try different settings of `sample-neighbor`, `neighbor-radius`, `shortest-word`, `max-word-length`, and `num-agents`.
## EXTENDING THE MODEL
* You may want to implement different ways of: sampling neighbors and sampling words for the sender
## NETLOGO FEATURES
`in-radius` to sample from radius.
## CREDITS AND REFERENCES
If you are using this netlogo model file then please cite:
Shubhanshu Mishra (2019). The Number Game. https://github.com/napsternxg/netlogo-models
The model was first presented in the paper: Baronchelli, A., Felici, M., Loreto, V., Caglioti, E., & Steels, L. (2006). Sharp transition towards shared vocabularies in multi-agent systems. Journal of Statistical Mechanics: Theory and Experiment, 2006(6), P06014–P06014. https://doi.org/10.1088/1742-5468/2006/06/p06014
## COPYRIGHT AND LICENSE
Copyright 2019 Shubhanshu Mishra.
![CC BY-NC-SA 3.0](http://ccl.northwestern.edu/images/creativecommons/byncsa.png)
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.
Commercial licenses are also available. To inquire about commercial licenses, please contact Shubhanshu Mishra at https://twitter.com/TheShubhanshu.
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