A client for pluggable board game implementations.
The client included here is designed to work with jbradberry/boardgame-socketserver and the Monte Carlo Tree Search implementation jbradberry/mcts.
- Python 2.7, 3.5+; PyPy; PyPy3
- six
To set up your local environment you should create a virtualenv and install everything into it.
$ mkvirtualenv boardgames
Pip install this repo, either from a local copy,
$ pip install -e boardgame-socketplayer
or from github,
$ pip install git+https://github.com/jbradberry/boardgame-socketplayer
To connect to a server as a human player playing (for example) Ultimate Tic Tac Toe
$ board-play.py t3 human $ board-play.py t3 human 192.168.1.1 8000 # with ip addr and port
To connect a client using one of the compatible Monte Carlo Tree Search AI players
$ board-play.py t3 jrb.mcts.uct # number of wins metric $ board-play.py t3 jrb.mcts.uctv # point value of the board metric
Configuration variables can be passed in using -e <variable
name>=<variable value>
. The -e
flag may be repeated to pass in
multiple variables. For example,
$ board-play.py t3 jrb.mcts.uct -e time=120 -e C=3.5
would configure the UCT player to use 2 minutes of thinking time, with an exploration coefficient of 3.5.
Compatible games that have been implemented include: