Starcraft AI blog

CherryPi remains interesting, although for now it still looks like Just Another Bot.

CherryPi wants to win with masses of zerglings, or occasionally hydralisks against protoss. It has some reactions, but overall tends to show a lack of strategic flexibility. It has a plan, but if the plan doesn’t work the followup tends to be slow and inadequate (compare Killerbot by Marian Devecka, which can completely switch its unit mix when a plan doesn’t work). Today’s game against LetaBot by Martin Rooijackers is an example. CherryPi opened with a fast second hatchery and no gas, to put on early pressure with masses of slow zerglings. LetaBot saw it coming and easily repelled the lings. CherryPi kept making masses of lings with few drones even after terran had medics and stim, when no quantity of slow zerglings could pose a threat. Terran played slowly and overcautiously, making easy-to-see mistakes, but it didn’t matter because the zerg strategy was inconsequent. By the time CherryPi started slowly adding mutalisks, mutalisks were also no threat. LetaBot eventually moved out and swept aside everything in its path. (Then LetaBot got stuck on the enemy ramp and crashed, or overstepped the time limit, but that’s a different lesson.)

CherryPi seems to make a lot of decisions without scouting. For example, it makes scourge (sometimes more than a little) when the enemy has no air tech. It moves its overlords, but does not send one to the enemy base. I think it is making choices based on units that it sees, especially versus protoss. But when it feels overmatched it holds its army well back from the enemy, meaning that it can’t see. Compare Steamhammer, which is aggressive and keeps its units forward even when it’s a big risk; the countervailing advantage is that it gets to see what the enemy has and what the enemy is doing.

Against zerg, CherryPi has different openings. If one loses, it tries the next. From what I’ve seen, the first opening is a 9 pool without gas, followed by a hatchery for mass slow zerglings. It’s a safe middle-of-the-road opening, or in other words halfhearted, but CherryPi loves its favorite. If that loses, the second try is sunken turtle into mutalisks, which is successful against many zergs (I think it is likely to work against Steamhammer too). There may be fancy learning going on behind the scenes, but if so we can’t see it because the tournament doesn’t have enough games.

Against protoss, I can’t detect any such progression in CherryPi’s openings. I think it’s always playing the same opening, and adapting it somewhat to the situation. It expands with 12 hatch, sunkens up its front, and makes massive numbers of drones. It’s similar to Killerbot’s plan, and a good one in general though the early sunkens are often unnecessary (and occasionally insufficient). The games against Bereaver make a good example; the first is a loss and the second a win, but zerg plays similarly in both. In the first game, notice how zerg keeps making mass drones and maintains a strong economy even as it is losing every fight, including losing its drones at a high rate. In the second game, the difference was that the players were at cross positions on a large map, and Bereaver’s corsair play and reaver drop were less effective.

CherryPi is safe against fast rushes; it has a perfect record so far against the zerg rushbots. CherryPi is vulnerable to hard rushes. Wuli won 2-0, and so did Flash which also does heavy early zealot pressure. Black Crow’s relentless zergling waves beat both the zergling opening and the turtle opening.

Overall, CherryPi has glaring weaknesses just like other bots do. But as I write, it is ranked #11, so it is strong by the standards of this tournament. I think the main source of its strength compared to other bots is the same as the main source of Steamhammer’s strength, the pressure style of play, which works because bots are better at attack than at defense. Steamhammer is ahead of CherryPi for now, because I invested effort in stability and resilience and lose fewer games to bugs and basic goofs. The CherryPi team is presumably investing in smarts instead, which should pay off in the long run. I haven’t seen any sign that CherryPi has particular smarts in opponent modeling—as far as I can see its opening learning is a simple algorithm, and I can’t detect anything else it might be doing—but if it does we might not be able to tell, because the tournament is not long enough.

The next AIIDE tournament may be interesting.