You'll need to symlink our environments into you OpenAI Gym installation.
First, install OpenAI Gym. You may need to checkout an older version of the gym:
git checkout 52e803f36b3281a575bf98255947a5a74d3c59a0
Once installed (using pip
), cd
into your installation and ln
the new env/
file into the OpenAI gym install directory:
cd /path/to/openaigym/gym/envs/safety;
ln -s /path/to/this/dir/env/acc.py acc.py
Also register this new environment by adding the following lines to gym/envs/__init__.py
:
register(
id='acc-v0',
entry_point='gym.envs.safety:ACCEnv',
max_episode_steps=200, # todo edit
reward_threshold=195.0, # todo edit
)
And add the appropriate import to gym/envs/safety/__init__.py
:
from gym.envs.safety.acc import ACCEnv
Finally, add a new method to gym/spaces/Discrete.py
:
def sample_restricted(self, filter_fn):
""" Sample from a subset of the space. """
subset = filter(filter_fn, range(0,self.n))
idx = prng.np_random.randint(len(subset))
return subset[idx]
Nathan Fulton 2017. GPLv2