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Hands-On Reinforcement Learning for Games
book

Hands-On Reinforcement Learning for Games

by Micheal Lanham
January 2020
Intermediate to advanced
432 pages
10h 18m
English
Packt Publishing
Content preview from Hands-On Reinforcement Learning for Games

Exploiting ML-Agents

At some point, we need to move beyond building and training agent algorithms and explore building our own environments. Building your own environments will also give you more experience in making good reward functions. We have virtually omitted this important question in Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL) and that is what makes a good reward function.

In this chapter, we will look to answer the question of what makes a good reward function or what a reward function is. We will talk about reward functions by building new environments with the Unity game engine. We will start by installing and setting up Unity ML-Agents, an advanced DRL kit for building agents and environments. From there, ...

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Publisher Resources

ISBN: 9781839214936