rescue-gridworld 1.0.5

A procedural gridworld maze requiring completion of temporally extended tasks.

Rescue Gridworld

This environment provides a Search and Rescue gridworld where the objective is to rescue all the people from the maze. To achieve this requires completion of a temporally extended sequence of tasks as follows.

• Exploration of the maze, opening locked doors to progress. Unlocking a door requires completion of the subtask sequence collect key -> unlock cupboard -> collect keycard -> unlock door.
• Talk to people discovered so they follow the agent, rescuing them. People are non-stationary within the environment moving randomly every 3 timestaps.
• The objective is to exit having rescued all the people, but it is also possible to exit without having done so.

Installation

pip install rescue_gridworld

Quick Start

You can run a random agent to test the environment by copying run_random_agent.py to a local directory and running:

python run_random_agent.py --render --steps 1000 --rooms 5

Manual Usage

import gymnasium as gym
import rescue_gridworld

env = gym.make("RescueGridworld-v0", render_mode="human", tile_size=tile_size, num_rooms=5)
obs, info = env.reset()
# ... step the env ...

Action Space

There are 9 actions in the environment:

• 0: Move up.
• 1: Move down.
• 2: Move left.
• 3: Move right.
• 4: Collect key.
• 5: Unlock cupboard.
• 6: Collect keycard.
• 7: Unlock door.
• 8: Talk to person.

Observation Space

The observation provides 2 7x7 "windows" (although this default can be changed by setting obs_window_size to any odd number when creating the environment).

• The first is a line-of-sight observation of the local environment.
• The second is a line-of-sight filtered set of "chain id's".

The Python definitions are as follows to allow the grid to be viewed as an image.:

    self.observation_space = spaces.Dict(
        {
            "grid": spaces.Box(low=0, high=255, shape=(1, 7, 7), dtype=np.uint8),
            "chain_grid": spaces.Box(low=-2, high=500, shape=(1, 7, 7), dtype=np.int16),
        }
    )

Rewards

Reward of 5 is given for completion of subtasks:

• Collect key.
• Unlock cupboard.
• Collect keycard.
• Unlock door.
• Talk to person.
• Exit.

An additional reward of 50 is given if all people have been saved before exiting.

A step penalty of -0.01 is applied to encourage efficiency.

Episode termination conditions

Episodes terminate after max steps, or if the agent moves onto the exit square.