Which framework is best for reinforcement learning?
Top 10 Frameworks For Reinforcement Learning An ML Enthusiast Must Know
- Acme. About: Acme is a framework for distributed reinforcement learning introduced by DeepMind.
- DeeR. About: DeeR is a Python library for deep reinforcement learning.
- Dopamine.
- Frap.
- Learned Policy Gradient (LPG)
- RLgraph.
- Surreal.
- SLM-Lab.
Which is the Python library for reinforcement learning?
Reinforcement Learning Library: pyqlearning. pyqlearning is Python library to implement Reinforcement Learning and Deep Reinforcement Learning, especially for Q-Learning, Deep Q-Network, and Multi-agent Deep Q-Network which can be optimized by Annealing models such as Simulated Annealing, Adaptive Simulated Annealing,…
Which is the best Python library for deep learning?
Pyqlearning is a library of Python which is used to implement Deep learning and Reinforcement learning. Specifically for Deep Q-Network, Multi-agent Deep-Q Network, and Q Learning which can be optimized by Annealing models. For instance, Adaptive Simulated Annealing, Simulated Annealing, Quantum Monte Carlo method.
How to use deep reinforcement learning in Python?
Deep Reinforcement Learning (Deep Q-Network: DQN) to solve Maze. Multi-agent Deep Reinforcement Learning to solve the pursuit-evasion game. The source code is currently hosted on GitHub. Installers for the latest released version are available at the Python package index. numpy: v1.13.3 or higher.
Which is the best tool for reinforcement learning?
Pyqlearning has a couple of examples for various tasks and two tutorials featuring Maze Solving and the pursuit-evasion game by Deep Q-Network. You may find them in the official documentation. The documentation seems incomplete as it focuses on the math, and not the library’s description and usage.