Skip to Main Content
Deep Reinforcement Learning Hands-On
book

Deep Reinforcement Learning Hands-On

by Oleg Vasilev, Maxim Lapan, Martijn van Otterlo, Mikhail Yurushkin, Basem O. F. Alijla
June 2018
Intermediate to advanced content levelIntermediate to advanced
546 pages
13h 30m
English
Packt Publishing
Content preview from Deep Reinforcement Learning Hands-On

Cross-entropy on FrozenLake

The next environment we'll try to solve using the cross-entropy method is FrozenLake. Its world is from the so-called "grid world" category, when your agent lives in a grid of size 4 × 4 and can move in four directions: up, down, left, and right. The agent always starts at a top-left position, and its goal is to reach the bottom-right cell of the grid. There are holes in the fixed cells of the grid and if you get into those holes, the episode ends and your reward is zero. If the agent reaches the destination cell, then it obtains the reward 1.0 and the episode ends.

To make life more complicated, the world is slippery (it's a frozen lake after all), so the agent's actions do not always turn out as expected: there is ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Grokking Deep Reinforcement Learning

Grokking Deep Reinforcement Learning

Miguel Morales

Publisher Resources

ISBN: 9781788834247Supplemental Content