# Solving Frozen Lake Using Monte Carlo

Frozen Lake is another simple game found in the OpenAI framework. This is a classic game where you can do sampling and simulations for Monte Carlo reinforcement learning. We have already described and used the Frozen Lake environment in *Chapter 05*, *Dynamic Programming*. Here we shall quickly revise the basics of the game so that we can solve it using Monte Carlo methods in the upcoming activity.

We have a 4x4 grid of cells, which is the entire frozen lake. It contains 16 cells (a 4x4 grid). The cells are marked as `S`

– Start, `F`

– Frozen, `H`

– Hole, and `G`

– Goal. The player needs to move from the Start cell, `S`

, to the Goal cell, along with the Frozen areas (`F`

cells), without falling into Holes (`H`

cells). The following figure visually presents the aforementioned information:

Here are some basic details of the game:

**The aim of the game**: The aim of the game...