🚀 go-pugleaf

Full story with video: 
<https://www.theverge.com/2017/4/3/15164490/alibaba-ai-starcraft-combat>

Last year, Alphabet’s DeepMind division captured the world’s attention 
by besting humanity’s top player in the game of Go. The achievement, 
which many experts predicted was still a decade off, showed the rapid 
progress being made in the world of artificial intelligence. DeepMind 
subsequently announced that its next goal in gaming was mastering 
StarCraft, a classic PC game that is a staple of competitive e-sports. 
Facebook also threw its hat in the ring, creating an open-source 
framework so that developers could work on solving StarCraft using the 
social network’s AI toolkit.

Now a team from China’s Alibaba has published a paper describing a 
system that learned to execute a number of strategies employed by 
high-level players without being given any specific instruction on how 
best to manage combat. Like many deep learning systems, the software 
improved through trial and error, demonstrating the ability to adapt to 
changes in the number and type of troops engaged in battle.

“BiCNet can handle different types of combats under diverse terrains 
with arbitrary numbers of AI agents for both sides. Our analysis 
demonstrates that without any supervisions such as human demonstrations 
or labelled data, BiCNet could learn various types of coordination 
strategies that is similar to these of experienced game players,” the 
authors wrote in a paper published to arXiv. “Moreover, BiCNet is easily 
adaptable to the tasks with heterogeneous agents. In our experiments, we 
evaluate our approach against multiple baselines under different 
scenarios; it shows state-of-the-art performance, and possesses 
potential values for large-scale real-world applications.”

This type of AI may one day compete in tournaments hosted by Alibaba 
itself. But like AI trained to play poker, the developers hope that this 
system, or least this type of system, will have a broad range of 
real-world applications beyond just beating humans at StarCraft. 
“Real-world artificial intelligence (AI) applications often require 
multiple agents to work in a collaborative effort. Efficient learning 
for intra-agent communication and coordination is an indispensable step 
towards general AI.” It will be extra ironic if a sentient, SkyNet type 
of artificial intelligence is one day created from a software program 
trained on virtual space marines.


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