RL Visualizer

RL Visualizer is a Python package for visualizing action probabilities, entropy, and rewards in reinforcement learning models.

Features

• Visualize action probabilities as bar charts
• Track entropy to monitor model uncertainty
• Plot per-step rewards within a single episode
• Compatible with Gym and Gymnasium environments

Installation

pip install rl-visualizer

Example

• Here you can see what rl_visualizer do in action:
• This is a custom highway simulated environment in Gymasium format
• Action space: is defined with this

- Enum class Action(Enum):
    NO_ACTION = 0
    CHANGE_LANE_RIGHT = 1
    CHANGE_LANE_LEFT = 2
    ACCELERATE = 3
    DECELERATE = 4
    EMERGENCY_BRAKE = 5

• Given reward for driving between 75km/h and 104km/h (max reward for 104km/h and driving not on leftmost lane)
• Given extra reward if driving not in the leftmost lane
• Given negative reward for near collisions and collisions. Near collision is calculated by ttc