Reinforcement Learning: Monte Carlo Method

In Reinforcement learning, the learner or the decision maker, called the Agent, constantly interacts with its Environment by performing actions sequentially at each discrete time step. Interaction of the Agent with its Environment changes the Environment's state, and as a result, the Agent receives a numerical reward from the Environment.

--

--

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Renu Khandelwal

Renu Khandelwal

5K Followers

Loves learning, sharing, and discovering myself. Passionate about Machine Learning and Deep Learning