Hands-On Machine Learning for Algorithmic Trading

Components of an interactive RL system

Solving complex decision problems usually requires a simplified model that isolates the key aspects. The following diagram highlights the salient features of an RL problem:

These typically include the following:

• Observations by the agent of the state of the environment
• A set of actions that are available to the agent
• A policy that governs the agent's decisions

In addition, the environment emits a reward signal that reflects the new state resulting from the agent's action. At the core, the agent usually learns a value function that shapes its judgment over actions. The agent has an objective function ...