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Learning in Normal-Form Games

This repo focuses on matrix games and learning algorithms.

What is implemented?

The implementation focuses on

  • Matrix Games

    • Randomly generated Matrix Games
    • Economic Games (complete-information auctions, contests, and oligopolies)
  • Learning Algorithms

    • Online Mirror Descent
    • tbd

Projects

Description
tbd
...

Setup

Note: These setup instructions assume a Linux-based OS and uses python 3.11 (or higher). Install virtualenv (or whatever you prefer for virtual envs) ``` sudo apt-get install virtualenv ``` Create a virtual environment with virtual env (you can also choose your own name) ``` virtualenv -p python3 venv ``` You can specify the python version for the virtual environment via the -p flag. Note that this version already needs to be installed on the system (e.g. `virtualenv - p python3 venv` uses the standard python3 version from the system).

activate the environment with

source ./venv/bin/activate

Install all requirements

pip install -r requirements.txt

Install the decomposition package.

pip install -e .

You can also run "pip install ." if you don't want to edit the code. The "-e" flag ensures that pip does not copy the code but uses the editable files instead.

Install pre-commit hooks (for development)
Install pre-commit hooks for your project

pre-commit install

Verify by running on all files:

pre-commit run --all-files

For more information see https://pre-commit.com/.

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Learning in (finite) Normal-Form Games

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