Bandit Model Research Simulations

This work begins by replicating the multi-armed bandit simulation of Posen & Levinthal (2012), "Chasing a Moving Target: Exploitation and Exploration in Dynamic Environments", Management Science 58(3), pp.587-601. It extends this into a general-purpose bandit simulation with additional variables that can be manipulated for further research.

Contributors

Joseph W Clark, University of Maine

File Structure

• All files in this directory (except README.md) define experiments.
• The output subfolder will hold the data and log output from simulation experiments.
• The analysis subfolder contains some sample scripts for visualizing the data with Python.
• Files in the bandito subfolder run the actual experiments:
  • /bandito/bandit.py runs one replication of a bandit simulation.
  • /bandito/banditexperiment.py runs an experiment with any specified set of treatments and number of replications.
  • /bandito/banditfunctions.py contains algorithms for turbulence, strategy, beliefs, and payoffs. To implement a new algorithm, place it there.

How to Use

Copy the file sample_experiment.py and modify to set up your experiment. Run it with something like the following:

python sample_experiment.py

Warning: You may want to change the number of replications for a faster test. Posen & Levinthal used 25000 replications for each experimental treatment, and replicating their experiments may take hours or days.

Tested on Mac OS X with Python 3.5.2