The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
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Computational framework for reinforcement learning in traffic control
- reinforcement-learning
- traffic-control
- benchmark
- autonomous
This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.