Spellcaster Control Agent in StarCraft II Using Deep Reinforcement Learning

Spellcaster Control Agent in StarCraft II Using Deep Reinforcement Learning

This paper proposes a DRL -based training method for spellcaster units in StarCraft II, one of the most representative Real-Time Strategy (RTS) games. During combat situations in StarCraft II, micro-controlling various combat units is crucial in order to win the game. Among many other combat units,...

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Bibliographic Details
Main Authors: Wooseok Song, Woong Hyun Suh, Chang Wook Ahn
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Electronics
Subjects:
deep reinforcement learning
A3C
game AI
StarCraft II
spellcaster
minigame
Online Access:https://www.mdpi.com/2079-9292/9/6/996

Internet

https://www.mdpi.com/2079-9292/9/6/996

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