Repository with code for strategy selection in StarCraft.

StarCraft is a complex game and players often resort to strategies (policies that map game states to actions). Here, we abstract game details and deal with strategy selection.

StarcraftNash project runs a round-robin tournament between strategy selection methods for StarCraft. In the tournament, methods play each other for a number of matches, selecting strategies that play a game of StarCraft. As strategy may interact in interesting forms (like rock-paper-scissors), it is useful to develop smart strategy selection methods.

Please read the wiki for a detailed discussion on how the software works and how you can implement and test your own strategy selection methods.

• NashPy: sudo -H pip2 install nashpy
• XlsxWriter: sudo -H pip2 install XlsxWriter

(assuming you have cloned the project and are located at project's root directory)

Run a tournament with 500 matches between Nash and Random Uniform methods, useing a default pool of matches and parameters.

python main.py -a nash -b random_uniform -i results_demo/fortress1000.txt -m 500

Accepted parameters are:

-i: File with the pool of matches (more information [here](wiki/Pool-of-matches))
-a: Strategy selection method for player a [optional if -t is supplied]
-b: Strategy selection method for player b [optional if -t is supplied]
-m: Number of matches between strategy selection methods
-t: Round-robin tournament with all the strategies
-s: Random seed for experiments
-r: Number of tournament repetitions
-e: Outputs tournament score chart to a .xls file given by this parameter
-oi: Output folder with intermediate results in CSV format of every tournament repetition
-or:'Output folder with the results in CSV format of every repetition of matches
-v: Verbose - prints informations about the games
-en: Parameter that defines the exploitation in an e-nash strategy
-eg: Defines the exploration in an e-greedy strategy
-sh: Shuffle the list of matches before each repetition
-p: Plot the results

Run tournament with experiment parameters given by a default .xml configuration file:

python main.py -c config/config_fortress.xml

Where -c specifies the path to the configuration file. Check this wiki page for instructions on how to specify parameters via the experiments configuration file.