In this chapter, we will introduce reinforcement learning (RL), which takes a different approach to machine learning (ML) than the supervised and unsupervised algorithms we have covered so far. RL has attracted enormous attention as the main driver behind some of the most exciting AI breakthroughs. We will see that the interactive and online nature of RL makes it particularly well-suited to the trading and investment domain.
RL is a computational approach to goal-directed learning performed by an agent that interacts with a typically stochastic environment which the agent has incomplete information about. RL aims to automate how the agent makes decisions to achieve a long-term objective by learning the value of states and actions from a reward signal. The ultimate goal is to derive a policy that encodes behavioral rules and maps states to actions.
RL is...
