Custom implemented Q_LEARNING agent playing on Taxi-v3
This is a trained model of an agent playing on the environment Taxi-v3. The agent was trained with a Q_LEARNING algorithm and evaluated for 100 episodes. See further agent and evaluation metadata in the according README section.
Import
The Python module used for training and uploading/downloading is rl-framework. It is an easy-to-read, plug-and-use Reinforcement Learning framework and provides standardized interfaces and implementations to various Reinforcement Learning methods and environments.
Also it provides connectors for the upload and download to popular model version control systems, including the HuggingFace Hub.
Usage
from rl_framework import CustomAgent, CustomAlgorithm
# Create new agent instance
agent = CustomAgent(
algorithm=CustomAlgorithm.Q_LEARNING
algorithm_parameters={
...
},
)
# Download existing agent from HF Hub
repository_id = "zap-thamm/QLearning-Taxi-v3"
file_name = "algorithm.pkl"
agent.download(repository_id=repository_id, filename=file_name)
Further examples can be found in the exploration section of the rl-framework repository.