Hands-On Machine Learning for Algorithmic Trading

The exploration-exploitation trade-off – the ε-greedy policy

ε-greedy is a simple policy that ensures the exploration of new actions in a given state while also exploiting the learning experience randomized the selection of actions. An ε-greedy policy selects an action randomly with a probability of ε, and the best action according to the value function otherwise.