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This repository hold results for tournaments made possible by the Axelrod-Project python library.

Tournament result

Standard tournament

Ranked violin plot

The mean utility of each player.

Payoffs

The pair wise utilities of each player.

Evolutionary dynamics

The evolutionary dynamic of the strategies (based on the utilities).

Wins

The number of wins of each player.

Payoff differences

The payoff differences for each player.

Pairwise payoff differences

The difference of payoffs between pairs of players.

Payoff Matrix

Here is a file with the payoff matrix.

Summary

Here is a file with the summary data.

Noisy tournament

Ranked violin plot

The mean utility of each player.

Payoffs

The pair wise utilities of each player.

Evolutionary dynamics

The evolutionary dynamic of the strategies (based on the utilities).

Wins

The number of wins of each player.

Payoff differences

The payoff differences for each player.

Pairwise payoff differences

The difference of payoffs between pairs of players.

Payoff Matrix

Here is a file with the payoff matrix.

Summary

Here is a file with the summary data.

Probabilistic ending tournament

Ranked violin plot

The mean utility of each player.

Payoffs

The pair wise utilities of each player.

Evolutionary dynamics

The evolutionary dynamic of the strategies (based on the utilities).

Wins

The number of wins of each player.

Payoff differences

The payoff differences for each player.

Pairwise payoff differences

The difference of payoffs between pairs of players.

Payoff Matrix

Here is a file with the payoff matrix.

Summary

Here is a file with the summary data.

Reproducing these results:

To reproduce these results you will need to install the axelrod library:

$ pip install axelrod

To reproduce these results run:

python run_noisy.py  # Run the noisy tournament
python run_std.py  # Run the standard tournament
python run_probend.py  # Run the probabilistic ending tournament

You can also run all three tournaments (in series):

python run_all.py

Note that this uses the installed version of the axelrod library. If you want to keep things tidy you can create a virtualenv and install the latest version of the library like so:

$ virtualenv env
$ source env/bin/activate
$ python -m pip install git+https://github.com/Axelrod-Python/Axelrod@master

If you have the Axelrod repository locally you can also run:

$ python -m pip install path_to_axelrod

If you have already installed axelrod you can add the [-U]{.title-ref} tag to update to the latest version of master:

$ python -m pip install git+https://github.com/Axelrod-Python/Axelrod@master -U

or:

$ python -m pip install path_to_axelrod  -U