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

Keras TensorFlow

Concepts

Deep Reinforcement Learning

Author (1)

Maxim Lapan

Collaboration by the tigers

The second experiment that I implemented was designed to make the tigers' lives more complicated and encourage collaboration between them. The training and play code are the same; the only difference is in the MAgent environment's configuration. I took the double_attack configuration file from MAgent (https://github.com/geek-ai/MAgent/blob/master/python/magent/builtin/config/double_attack.py) and tweaked it to add the reward of 0.1 after every step for both tigers and deer. The following is the modified function config_double_attack() from Chapter25/lib/data.py:

def config_double_attack(map_size):
    gw = magent.gridworld
    cfg = gw.Config()
    cfg.set({"map_width": map_size, "map_height": map_size})
    cfg.set({"embedding_size": 10})

We create the configuration object and set the map dimensions. The embedding size is the dimensionality of the minimap, which is not enabled in this configuration...

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Deep Reinforcement Learning Hands-On. - Second Edition

Published in: Jan 2020Publisher: PacktISBN-13: 9781838826994

Author (1)

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

Collaboration by the tigers

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Author (1)

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