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You're reading from  Deep Reinforcement Learning Hands-On. - Second Edition

Product typeBook
Published inJan 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781838826994
Edition2nd Edition
Languages
Python
Tools
KerasTensorFlow
Concepts
Deep Reinforcement Learning
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Author (1)
Maxim Lapan
Maxim Lapan
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Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan

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Policy experiments

The first model that I trained was with the Height objective and without zeroing the yaw component. A video of the robot executing the policy is available here: https://www.youtube.com/watch?v=u5rDogVYs9E. The movements are not very natural. In particular, the front-right leg is not moving at all. This model is available in the source tree as Chapter18/hw/libhw/t1.py.

As this might be related to the yaw observation component, which is different during the training and inference, the model was retrained with the --zero-yaw command-line option. The result is a bit better: all legs are now moving, but the robot's actions are still not very stable. The video is here: https://www.youtube.com/watch?v=1JVVnWNRi9k. The model used is in Chapter18/hw/libhw/t1zyh.py.

The third experiment was done with a different training objective, HeightOrient, which not only takes into account the height of the model, but also checks that the body of the robot is parallel to the...

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Deep Reinforcement Learning Hands-On. - Second Edition
Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994
© 2020 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Maxim Lapan

Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems, RL for web crawling and web pages analysis. He has been living in Germany with his family.
Read more about Maxim Lapan

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