Title
Evolutionary Machine Learning for RTS Game StarCraft.
Abstract
Real-Time Strategy (RTS) games involve multiple agents acting simultaneously, and result in enormous state dimensionality. In this paper, we propose an abstracted and simplified model for the famous game StarCraft, and design a dynamic programming algorithm to solve the building order problem, which takes minimal time to achieve a specific target. In addition, Genetic Algorithms (GA) are used to find an optimal target for the opening stage.
Year
Venue
Field
2017
THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE
Computer science,Artificial intelligence,Machine learning
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Lianlong Wu131.41
Andrew Markham251948.34