This package is an extensions of OpenAI Gym, for Partially Observable Markov Decision Process.
- Python
- OpenAI Gym
- PyGame
Check out the latest code
git clone https://github.com/d3sm0/gym_pomdp.git
To use it as a package simply run:
python setup.py install
Import the library and gym as and call the environment:
import gym
import gym_pomdp
env = gym.make("Tag-v0")
All environments are parametrized as in the original papers. In order to get larger state space or more enemies, it's easy to change the board_size in the specific environment.
- Tag
- Tiger
- BattleShip
- Network
- RockSample
General overview POMCP solver Point-based value iteration Similar work
David Silver and Joel Veness made this possible by releasing the code POMCP open source. And @manuel for proof test.
- Add pocman environment [WIP]