| property | value |
|---|---|
| Action Space | Discrete(5, int) |
| Observation Shape | Box(4, 48, 48) for |
| Observation Range | (-1, 1) for gray (0, 255) for state_pixels |
| Import | gym.make("CarRacingPLS-v1") |
Inherits the CarRacing environment (gym.envs.box2d.car_racing) but with discrete control instead of continuous one and a simpler observation space.
State consists of four consecutive images of STATE_W x STATE_H pixels. If the
render mode is state_pixels, the states are in colors. If the render mode is
gray, the states are in grayscale.
The reward is -0.1 every frame and +1000/N for every track tile visited, where N is the total number of tiles visited in the track. For example, if you have finished in 732 frames, your reward is 1000 - 0.1*732 = 926.8 points.
The game is solved when the agent consistently gets 900+ points. The track in all episodes are the same, generated at initialization.
The episode finishes when all the tiles are visited. The car also can go outside of the PLAYFIELD - that is far off the track, then it will get -100 and die.
pip install -e .Parameters for the environment.
seed: the seed of the environment.verbose: if the value is one, print debug information.render_mode: determines the state space. If the value isstate_pixelsthen the states are in colors. If the value isgray, then the states are in grayscale.