README.md

metadata

title: FrozenSlippery Q-Table Model
emoji: ❄️
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 5.9.1
app_file: app.py
pinned: false

FrozenSlippery Q-Table Model

This repository contains the trained Q-table model for the FrozenSlippery environment. It uses Q-learning to optimize the agent's performance in a reinforcement learning setup. The Q-table is stored as a .npy file and is used to predict actions for the agent based on its state.

Files

• frozenslippery_q_table.npy: The saved Q-table of the trained model.
• app.py: The application file to run the model and interact with the environment (if applicable).

How to Use

1. Clone the repository or pull the latest version to get the trained Q-table.
2. Use the Q-table in your reinforcement learning setup or interface with the provided app.

Example Usage:

To load the Q-table and use it in your environment, run the following:

import numpy as np

q_table = np.load('frozenslippery_q_table.npy')
# Use q_table in your environment setup