Starcraft AI blog

I watched some CherryPi games to see how it plays.

versus terran

CherryPi scored 92% against the 4 terrans. How did that happen?

Well, only 2 of the terrans are strong by CherryPi’s standard, and it pre-learned openings against both of them. Against #3 Iron, CherryPi played a mass zergling opening. In games where Iron did not wall, game over. What made it work is that, if Iron did build a wall, CherryPi understood when the wall was open or closed. That’s good cleverness. The zerglings formed a concave so they themselves were safe from the defenders behind the wall and nothing of Iron’s could sneak through, then when the barracks lifted to open the wall, rushed in and rampaged. Against #12 LetaBot, CherryPi played the same zergling opening and won by sheer persistence in attacking.

Both Iron and LetaBot could have won with little risk by playing more cautiously.

Against the weaker terrans, #16 IceBot and #25 HannesBredberg, CherryPi’s learning quickly found winning builds. Against IceBot it settled on a slow-moving mutalisk build with too many hatcheries, powering drones while IceBot delayed moving out. It’s the only case I found where CherryPi tries to win eventually instead of quickly. The games are consistent wins but are not impressive. Against HannesBredberg it was the mass lings again.

the learning sequence

Except against the 5 opponents for which it pre-learned openings, CherryPi opened the first game versus each opponent with 4 pool. It succeeded against refreshingly few of them. If that didn’t work, it tried another opening, and another, and so on. Most of the openings are of the low econ “I’ll just run you over in 6 minutes” kind.

CherryPi apparently tries all its openings without worrying whether they are appropriate to the matchup. It tried a lurker opening in this game versus Microwave. It made no sense to me, but maybe some zerg bots are vulnerable to lurkers.

CherryPi’s favorite unit is the zergling. Occasionally mutalisks or lurkers do something essential, but most of the time, early game or late, it wants to win with lings.

the Steamhammer family

#10 Steamhammer upset #6 CherryPi 72-32. The random openings worked as intended and baffled CherryPi’s learning. CherryPi has openings that could have won the majority of games (it won 7 of the first 10), but it could not find them (it won 3 of the last 10). It could not hear the learning signal over the noise.

Steamhammer forks cpac, Microwave, and Arrakhammer also had plus scores versus CherryPi. I doubt they were all for the same reason.

Next: Cpac.