Snake Environment 🐍#
We provide here an implementation of the Snake environment from (Bonnet et al., 2021). The goal of the agent is to navigate in a grid world (by default of size 12x12) to collect as many fruits as possible without colliding with its own body (i.e. looping on itself).
Observation#
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grid: jax array (float) of shape(num_rows, num_cols, 5), feature maps (image) that include information about the fruit, the snake head, its body and tail. -
step_count: jax array (int32) of shape(), current number of steps in the episode. -
action_mask: jax array (bool) of shape(4,), array specifying which directions the snake can move in from its current position.
Action#
The action space is a DiscreteArray of integer values: [0,1,2,3] -> [Up, Right, Down, Left].
Reward#
The reward is +1 upon collection of a fruit and 0 otherwise.
Registered Versions 📖#
Snake-v1: Snake game on a board of size 12x12 with a time limit of4000.