Starcraft AI blog

The planned post about strategy abstraction is delayed by a power outage at my house. Here’s a brief filler.

TeamLiquid has a post with analysis of new ASL maps Sparkle and Transistor by Australian protoss Legionnaire. Without drawing any strong conclusions about overall balance, Legionnaire points out how map features will affect play.

Current bots are poor at adapting to map features. More than that, it is beyond the state of the art for any AI system to adapt to maps with as few games as humans need. Humans reason out how map features affect play, and with experience they sharpen their reasoning. Machines, so far, mainly collect statistics about the course of events, and they need a vastly larger number of games to zero in on good strategy. Of course they may be able to play those many games faster, but we don’t know how to make a system that can combine reasoning with empirical learning like a human. I’m interested in Legionnaire’s expert analysis as an example that may offer clues.