airgym


Nameairgym JSON
Version 0.0.5 PyPI version JSON
download
home_pagehttps://github.com/zacjiker/airgym
SummaryOpenAI Gym environment for training reinforcement learning agents on an XPlane simulator
upload_time2023-03-27 15:27:55
maintainer
docs_urlNone
authorSAUVECANNE, Baptiste
requires_python>=3.6
licenseGPL-3.0
keywords openai gym xplane reinforcement learning rl environment ai artificial intelligence machine learning ml
VCS
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Travis-CI No Travis.
coveralls test coverage No coveralls.
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# XPlane Gym Environment

This project provides an OpenAI Gym environment for training reinforcement learning agents on an XPlane simulator. The environment allows agents to control an aircraft and receive rewards based on how well they perform a task, such as flying a certain trajectory or landing safely.

## Installation

To install the package, run the following command:

```bash
  pip install airgym
```
    
## Usage/Examples

To use the environment in your Python code, you can import it as follows:

```python
import airgym
import gym

# If XPlane is running on the same machine, you can use the default address and port. 
# Or, set ip address and port according to your configuration.
env = gym.make('AirGym-v1')

episods = 0

for episod in range(episods):
    obs = env.reset()
    done = False

    while not done:
        actions = env.action_space.sample()
        obs, reward, done, info = env.step(action)

env.close()
```

            

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