What is OpenSpiel?¶
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. OpenSpiel also includes tools to analyze learning dynamics and other common evaluation metrics. Games are represented as procedural extensive-form games, with some natural extensions.
Open Spiel supports
Single and multi-player games
Fully observable (via observations) and imperfect information games (via information states and observations)
Stochasticity (via explicit chance nodes mostly, even though implicit stochasticity is partially supported)
n-player normal-form “one-shot” games and (2-player) matrix games
Sequential and simultaneous move games
Zero-sum, general-sum, and cooperative (identical payoff) games
The games and utility functions (e.g. exploitability computation) are written in C++. These are also available using pybind11 Python bindings.
The methods names are in
CamelCase in C++ and
snake_case in Python (e.g.
state.ApplyAction in C++ will be
state.apply_action in Python). See the
pybind11 definition in open_spiel/python/pybind11/pyspiel.cc
for the full mapping between names.
For algorithms, many are written in both languages, even if some are only available from Python.
OpenSpiel has been tested on Linux (Ubuntu and Debian), MacOS. There is limited support for on Windows 10.
Visualization of games
There is a basic visualizer based on graphviz, see open_spiel/python/examples/treeviz_example.py.
There is an interactive viewer for OpenSpiel games called SpielViz.