Computational Model Library

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

Release Notes

First version - model implementation and exploratory data analysis

Version Submitter First published Last modified Status
1.0.0 Vinicius Ferraz Fri Dec 2 09:23:40 2022 Fri Dec 2 09:23:40 2022 Published Peer Reviewed https://doi.org/10.25937/q2xt-rj46

Discussion

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