In a reinforcement learning problem, an Actor or an Agent takes different decisions in an environment, with the goal of maximizing the total of the rewards it obtains from the environment in response ...

The tutorials lead you through implementing various algorithms in reinforcement learning. All of the code is in PyTorch (v0.4) and Python 3. Dynamic Programming: Implement Dynamic Programming ...

Deep Reinforcement Learning. Deep reinforcement learning. Background. Deep learning is a new research track within the field of machine learning . The main idea behind deep learning is to create ...

While deep reinforcement learning (RL) has fueled multiple high-profile successes in machine learning, it is held back from more widespread adoption by its often poor data efficiency and the limited ...

ABSTRACT: Single-agent reinforcement learning (RL) is commonly used to learn how to play computer games, in which the agent makes one move before making the next in a sequential decision process.