Starcraft AI blog

New zerg bot Monster has been going Godzilla on the opposition. As I write, it has 58 wins and 4 losses on BASIL (since it is unranked, it is facing opponents of all levels). Its wins include tough enemies like Iron (on Circuit Breaker). Its win rate on SSCAIT is “only” 31-8 as it is being voted tougher opponents on average. The losses on BASIL are to PurpleWave, Krasi0 (twice), and the expert zealot rusher Wuli.

I have yet to see Monster vary its early game build orders, though perhaps it simply hasn’t lost enough games to feel the need to. Versus terran, Monster likes three hatch mutalisk, making only one pair of zerglings at first. Krasi0 earned its 2 wins with proxy rax, beating the greedy build with fast aggression. Against protoss, Monster likes overpool followed by 11 hatchery, a standard build. It gets a hydra den early but does not always make use of it. Here is a win over Locutus where it does make hydras. Versus zerg, Monster likes overpool 9 gas, also one of Steamhammer’s favorite starts and difficult for bots to counter.

Monster is a complex bot with many skills. It appears to adapt its army size, unit mix, and static defense to the game situation. It has nice micro with zerglings, hydralisks, mutalisks, and scourge. (Though I judge McRaveZ’s muta micro is better. See this loss vs McRaveZ from SSCAIT; Monster won the rematch.) It can make queens with broodling, though I haven’t seen it make defilers. It knows how to position a sunken and block its ramp with zerglings to stop a vulture runby cold; see the Iron game above. Like ZZZKBot, when scouting for the location of a zerg opponent, it knows to discount a base when it does not see the creep; it does not have to scout farther to see that there is no hatchery. (See this win over Microwave for an example; watch how early the overlord turns away from its first scouting destination. Also notice Monster’s zergling formations.)

Monster still has a lot of headroom. I immediately saw inefficiencies in its build orders and weaknesses in its play. Its results say that its strengths are bigger than its weaknesses, though. I imagine it must have been thoroughly tested against a range of opponents to gain so many skills with such small loopholes.

Monster gg’s early when losing. I haven’t seen another bot surrender as quickly. There is an advantage to giving up early in testing: You can get more games in, iterate faster, and end up with a stronger bot. Of course the advantage doesn’t show in serious games, but if the gg is accurate then it doesn’t hurt.

Peering into the binary, I am impressed with Monster’s scope. The file I downloaded from SSCAIT is a 2.8MB .exe, pointing to a complex project that must have taken a long time to develop. It uses BWEB. I see a JSON parsing library and signs of a config file that is not included in the SSCAIT download. I see strings suggesting many skills that I have not yet noticed in games, such as scarab dodging.