pyrorl 0.0.2

An RL OpenAI Gym Environment for Wildfire Evacuation

Wildfire Evacuation RL Gym Environment

A new reinforcement learning OpenAI Gym environment built for the simulation of wildfire evacuation. Check out the docs and the demo.

How To Use

First, install our package:

pip install wildfire-evac

To use our wildfire evacuation environment, define the dimensions of your grid, where the populated areas are, the paths, and which populated areas can use which path. See an example below.

# Create environment
kwargs = {
    'num_rows': num_rows,
    'num_cols': num_cols,
    'populated_areas': populated_areas,
    'paths': paths,
    'paths_to_pops': paths_to_pops
}
env = gymnasium.make('wildfire_evac/WildfireEvacuation-v0', **kwargs)

# Run a simple loop of the environment
env.reset()
for _ in range(10):

    # Take action and observation
    action = env.action_space.sample()
    observation, reward, terminated, truncated, info = env.step(action)

    # Render environment and print reward
    env.render()
    print("Reward: " + str(reward))

For more examples, check out examples/.