Computational Model Library

Dynamic Equilibria Prediction: Experience-Weighted Attraction (EWA), Python Implementation (1.0.0)

This project is based on a Jupyter Notebook that describes the stepwise implementation of the EWA model in bi-matrix ( 2×2 ) strategic-form games for the simulation of economic learning processes. The output is a dataset with the simulated values of Attractions, Experience, selected strategies, and payoffs gained for the desired number of rounds and periods. The notebook also includes exploratory data analysis over the simulated output based on equilibrium, strategy frequencies, and payoffs.

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Release Notes

First version - model implementation and exploratory data analysis

Associated Publications

Dynamic Equilibria Prediction: Experience-Weighted Attraction (EWA), Python Implementation 1.0.0

Submitted by Vinicius Ferraz Published Dec 02, 2022 Last modified Dec 22, 2022
game theory Agent based social simulation

This project is based on a Jupyter Notebook that describes the stepwise implementation of the EWA model in bi-matrix ( 2×2 ) strategic-form games for the simulation of economic learning processes. The output is a dataset with the simulated values of Attractions, Experience, selected strategies, and payoffs gained for the desired number of rounds and periods. The notebook also includes exploratory data analysis over the simulated output based on equilibrium, strategy frequencies, and payoffs.

Release Notes

First version - model implementation and exploratory data analysis

Cite this Model

Vinicius Ferraz (2022, December 02). “Dynamic Equilibria Prediction: Experience-Weighted Attraction (EWA), Python Implementation” (Version 1.0.0). CoMSES Computational Model Library. Retrieved from: https://doi.org/10.25937/q2xt-rj46

References

https://doi.org/10.1111/1468-0262.00054

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Contributors
Vinicius Ferraz
DOI

10.25937/q2xt-rj46

Model Version
1.0.0
License
CC-BY-4.0
Programming Language
Python 3
Software Framework
Jupyter Notebook
Operating System
Mac OS
Publish Date
Friday, December 02, 2022
Last Updated
Thursday, December 22, 2022
Downloads 28
Peer Reviewed
Open Code Badge
Version Submitter First published Last modified Status
1.0.0 Vinicius Ferraz Fri Dec 2 09:23:40 2022 Thu Dec 22 16:18:55 2022 Published Peer Reviewed https://doi.org/10.25937/q2xt-rj46

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