Starcraft AI blog

Microwave’s history files include large doses of training data prepared before the tournament. I snipped that data out, so the tables here include only tournament games and the 7 post-tournament games that are excluded from the official results.

Microwave has many strategies. I counted 79, compared to 73 last year (my first impression was that there were many more this year, but it was not true). Like Steamhammer, when losing badly it flails, trying anything.

See NakedExpand in the enemy table: Microwave was able to punish BananaBrain when BananaBrain made nexus before cannons. It’s a theme. I think it indicates general aggressiveness or rushiness in the early game. I get 6:52 for Microwave’s median game length when defeating BananaBrain.

Microwave had 3 builds that scored above 50%, and others that were close, but experimented too much. It would have scored much higher if it had exploited more and explored less. I think the lesson is that the learning algorithm’s exploration parameter should be set depending on the opponent’s expected strength. If you’re expecting to score 35% and you find a choice that scores 60%, reduce your exploration and exploit the winner unless and until the opponent adapts. If you have more than one high-scoring build (and they’re not too much alike), switch between them and your opponent will have more trouble adapting. If you’re expecting to score 70%, keep exploring if your best choice is only 60%.

Even against a higher-finishing zerg, Microwave punishes the fast expansion when it recognizes it. It’s striking. Zerg is not able to add static defense to a base before the base finishes, so this ability to restrict the oppoent’s strategy could be even more powerful in ZvZ.

And against terran, too. Against Microwave, if expanding early, apparently terran and protoss should add defenses at the natural first.

The first opponent that Microwave outscored, and it was a runaway. Steamhammer struggled versus DaQin, but the other zergs were fine. Later I’ll examine why to see if there are lessons for Steamhammer.

The strong results against NakedExpand show here too.

Like McRave but apparently for a different reason, Microwave had unnecessary trouble with UAlbertaBot. It takes more than a simpleminded learning algorithm to adapt to a random opponent with such different rushes for each race. The ideal answer is to adapt during the game after scouting. Steamhammer’s answer is a super-turtle build that defeats all of UAlbertaBot’s rushes. But still, see that 100% next to NakedExpand?