Freeway#

This environment is part of the Atari environments. Please read that page first for general information.


Action Space	Discrete(18)
Observation Space	(210, 160, 3)
Observation High	255
Observation Low	0
Import	`gym.make("ALE/Freeway-v5")`

Description#

your objective is to guide your chicken across lane after lane of busy rush hour traffic. You receive a point for every chicken that makes it to the top fo the screen after crossing all the lanes of traffic. Detailed documentation can be found on the AtariAge page.

Rewards#

The exact reward dynamics depend on the environment and are usually documented in the game’s manual. You can find these manuals on AtariAge.

Atari environments are simulated via the Arcade Learning Environment (ALE) [1].

Action Space#

The action space a subset of the following discrete set of legal actions:

Num	Action
0	NOOP
1	FIRE
2	UP
3	RIGHT
4	LEFT
5	DOWN
6	UPRIGHT
7	UPLEFT
8	DOWNRIGHT
9	DOWNLEFT
10	UPFIRE
11	RIGHTFIRE
12	LEFTFIRE
13	DOWNFIRE
14	UPRIGHTFIRE
15	UPLEFTFIRE
16	DOWNRIGHTFIRE
17	DOWNLEFTFIRE

If you use v0 or v4 and the environment is initialized via make, the action space will usually be much smaller since most legal actions don’t have any effect. Thus, the enumeration of the actions will differ. The action space can be expanded to the full legal space by passing the keyword argument full_action_space=True to make.

The reduced action space of an Atari environment may depend on the flavor of the game. You can specify the flavor by providing the arguments difficulty and mode when constructing the environment. This documentation only provides details on the action spaces of default flavors.

Observations#

By default, the environment returns the RGB image that is displayed to human players as an observation. However, it is possible to observe

The 128 Bytes of RAM of the console
A grayscale image

instead. The respective observation spaces are

Box([0 ... 0], [255 ... 255], (128,), uint8)
Box([[0 ... 0] ... [0 ... 0]], [[255 ... 255] ... [255 ... 255]], (250, 160), uint8)

respectively. The general article on Atari environments outlines different ways to instantiate corresponding environments via gym.make.

Arguments#

env = gym.make("ALE/Freeway-v5")

The various ways to configure the environment are described in detail in the article on Atari environments.

Environment	Valid Modes	Valid Difficulties	Default Mode
Freeway	`[0, ..., 7]`	`[0, 1]`	`0`

You may use the suffix “-ram” to switch to the RAM observation space. In v0 and v4, the suffixes “Deterministic” and “NoFrameskip” are available. These are no longer supported in v5. In order to obtain equivalent behavior, pass keyword arguments to gym.make as outlined in the general article on Atari environments. The versions v0 and v4 are not contained in the “ALE” namespace. I.e. they are instantiated via gym.make("Freeway-v0").

Version History#

A thorough discussion of the intricate differences between the versions and configurations can be found in the general article on Atari environments.

Version	`frameskip=`	`repeat_action_probability=`	`full_action_space=`
v0	`(2, 5,)`	`0.25`	`False`
v4	`(2, 5,)`	`0.0`	`False`
v5	`5`	`0.25`	`True`

Version v5 follows the best practices outlined in [2]. Thus, it is recommended to transition to v5 and customize the environment using the arguments above, if necessary.