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

Results

Let’s now take a look at the results.

The feed-forward model

The convergence on Yandex data for one year requires about 10M training steps, which can take a while (GTX 1080Ti trains at a speed of 230-250 steps per second). During training, we have several charts in TensorBoard showing us what’s going on.

The following are two charts, reward_100 and steps_100, with average reward (which is in percentages) and the average length of the episode for the last 100 episodes, respectively:

The feed-forward model

Figure 3: The reward plot for the feed-forward version

The charts show us two good things:

  1. Our agent was able to figure out when to buy and sell the share to get positive ...
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