Starcraft AI blog

New bot Stardust (here is its BASIL stats page) is a development of Locutus by another name, by the same author, Bruce Nielsen. I don’t know why the name was changed, especially since the DLL name is still Locutus.dll, the name configured in the config file is still “Locutus”, and the SSCAIT comment says “it will only play as Stardust on SSCAIT. If downloaded it will play as Locutus.” That seems like a confusing choice. It is entered as Stardust in CoG 2020, though. Locutus classic is disabled on SSCAIT.

The most immediate change is that Stardust is updated to BWAPI 4.4.0. The DLL became smaller, perhaps due to dropping libraries.

It is usually difficult to notice changes in a bot’s play by watching games; a change may be obvious if you know what to look for, but invisible if you aren’t ready to see it. Nevertheless, I watched some Locutus and Stardust games and saw an unmistakable difference: Army maneuvering has been improved from UAlbertabot-style moving back and forth along a line to tscmoo-style keeping a constant distance from the enemy front. Keeping a constant distance means that you automatically form up into a concave when possible; when combat starts, whether in attack or defense, units are able to open fire almost simultaneously, with no maneuvering into position, so you do more shooting and less moving and kill enemies faster. It’s a big change and I expect it must have been in gestation for a long time.

There are disadvantages to the tscmoo style, but overall, Stardust’s formed-up armies should outdo Locutus’s jumble of units by far. I expect Stardust to reach a higher elo.

With a big change like that, there are likely smaller changes too that I did not see. I didn’t archive a recent Locutus version to compare, so I can’t draw a final balance. Comparing with the CoG 2019 version from a year ago, I can see some of the features added in the past year: Center proxies, a dedicated squad to chase down the enemy scout, the choke (as opposed to the wall) as a building location. But I don’t think any of those are recent additions.

My forecast: We used to think Locutus was scary. Now we’ll learn better.

Thanks to SCHNAIL we’re starting to see bot matches against strong human players. Today I write about the Cadenzie (Z) 5 game match versus Locutus from last Tuesday. It comes with an interview on Making Computer Do Things. Watch the games first if you’re interested.

Cadenzie is not a top pro; to me her play looks a little slow and awkward compared to the best. But she is very strong, and when the match was announced, I expected her to win every game. In the event, she scored 3-2. I thought all the games were one-sided: Either zerg won fairly easily, or else Locutus collected enough dragoons and was able to overpower her hydralisks with superhuman dragoon micro. In the game where Locutus chose to go zealots instead, the zealots looked wimpy; Steamhammer has had the same experience.

I also felt that the first game was the only one that Cadenzie played with 100% seriousness (and she said as much in the interview). She played a well-rehearsed build with mass hydras and drop. Locutus (lacking PurpleWave’s strategy skills) did not understand how to read her build in order to cut corners in the opening, and it fell behind (slightly behind in bot terms, “massively” behind according to Cadenzie—the distance varies by skill level!). When hydras collected outside its natural, Locutus trickled units out through the narrow opening in its wall and let them be picked off, falling further behind. The front gateway fell, and then overlord speed finished. She’d gotten overlord drop first, and she picked up hydras and put them in the protoss main, where they cleaned up with little effort. I judged that she could as easily have skipped drop and powered through the front door.

I thought the most interesting answer in the interview was “I played in a tournament before where there was a team melee relay style with a mix of progamers and beginner level players and they would take turns every 2 minutes, in a way it was most similar to that.” In other words, Locutus was extremely good at some aspects of the game, and extremely weak at others. That is similar to other games where computer programs were good enough to play humans and not good enough to win every time; for example, chess programs in the old days were superhuman at tactics and weak at strategy in a very similar way.

She repeatedly emphasized that bots need to adapt more to what they scout. I think that’s the main takeaway.

Compare Artosis versus top bots on Twitch: Notice how often Artosis says “In this build, when I see such-and-such, I do so-and-so.” Human players have extensive knowledge of how to play in specific situations, and no bot comes close. SAIDA may come closest, with its one all-purpose build and numerous reactions, but its understanding is shallow by comparison. PurpleWave I think has the greatest strategy knowledge of any bot, but it has a weak understanding of tactics. Locutus relies on its strong micro and aggressive tactics, which cover for the weaknesses in other aspects. Bots not only know less, they don’t integrate their knowledge into a theory of how the game works—they don’t understand what they know, so they a weak at drawing inferences and their adaptation ability is shallow. See for example the Artosis game versus Killerbot by Marian Devecka, where Artosis was able to guess that a third zerg base at an early timing was likely, and scouted for it specifically. In other games, he did not spend effort scouting for expansions he did not see as likely.

By the way, the last game is the best, Artosis vs McRave starting at ~2 hours in.

Filling the knowledge gap I believe will require machine learning. Writing rules and reactions by hand will take a day or two less than forever, and search will not solve all problems if it has only handmade evaluations to rely on. For Steamhammer, I’ve figured out a way to put together familiar algorithms that will execute fast, and I expect it will also learn fast (from little data) and be reasonably accurate (not amazing like deep learning, but adequate). It’s part of my strategy adaptation goal. If it works as well as I hope, I WILL CRUSH YOU PUNY MORTALS BENEATH MY STEEL THUMB BWAHAHAHAHA, or something like that. Actually the first application will be nothing more than an evaluation function to choose openings and strategies, valuable but extracting only a little of the potential, and if it’s successful then after I explain how it works everyone else will get ahead of me again. That will be good too.

Locutus’s game records are in almost the same format as Steamhammer’s and can be summarized by the same script. I expect it will also work for DaQin and AITP.

Where Steamhammer was set to keep 100 game records per opponent, Locutus was set to keep 200. Since there were 100 rounds in the tournament, game counts over 100 mean that pre-learned data is included in the table alongside the tournament data. If Locutus was not trained on a near-final version of the opponent, then the two could be significantly different.

After seeing a few Locutus-PurpleWave games I got the impression that PurpleWave reacted adequately to Locutus’s trick strategy of cannoning the ramp and then dropping zealots. So I was surprised that Locutus considered it the best choice. But the overall win rate is high compared to the tournament results, so I suspect it is influenced by pre-learned data from games against a weaker version of PurpleWave.

The numbers in the “recognized” columns of the plan table show how widely Steamhammer cast its net for a solution to Locutus.

Locutus never tried to steal the gas of a zerg. Objectively, that makes sense. In the context of bot play, I’m not so sure; many bots of all races mess up their builds in the face of a gas steal.

Locutus declared an enemy-specific strategy against Iron. I’m not sure why it also had pre-learned data.

Proxy DT rush. That tends to confirm my picture of XiaoYi as vulnerable to tricks.

Locutus configured an enemy-specific strategy against UAlbertaBot. Openings other than CannonFirst4GateGoon are from pre-learned data, which was ignored in making the opening decision.

Yesterday’s game Simplicity vs Locutus on Andromeda on BASIL starts out as one of the most entertaining bot games I have seen. The pictures show some of the cool stuff that Simplicity tried—with success. Then, after a tremendous fight where each side pressed temporary advantages and maxed its army, the replay loses sync and OpenBW cannot show the last half of the game.

Queens with broodling. The Research tab shows broodling research, and there are broodlings on the ground. Simplicity made 8 queens early and even researched queen energy, and the queens paid for themselves with interest. When Locutus attacked, zerg sent out as many queens as had energy to simultaneously spawn broodlings, helping to break the attacks. It’s a simple way to coordinate the queens to get tactical results, and is more effective than the common bot approach of using the queens as attrition weapons. Simplicity’s queens eventually died to corsairs; with more careful play, they could have lived to the end of the game, because Locutus was not skilled with its corsairs.

Island base with static defense. The overlord on the left has just dropped off another drone to join the miners.

Drops. Simplicity repeatedly dropped small numbers of units into the far end of Locutus’s base, and Locutus did not react properly. The drops were not decisive, but were cost-effective.

Both sides maxed their supply, or nearly so. At that point, Locutus had better upgrades but Simplicity had a larger army. Locutus could not keep its natural safe. Luckily for protoss, it was already mined out.

But Locutus had a stronger economy with more bases and a large bank of resources, and Simplicity ran out of resources. The desync hides the end of the game, which timed out after an hour. I believe that Locutus wiped out all zerg it could reach on the ground, and then had no answer for the island base. When the game timed out, BASIL gave the win to Simplicity on points. Moral: You need at least enough island skills to make air units to attack inaccessible bases.

The Locutusoids have learning data only slightly different from Steamhammer’s. I have run my summarizer code for CSE, BlueBlueSky, Locutus, and ISAMind, skipping DaQin because it recorded only 1 game per opponent (which tickles a bug in my code). I am thinking of posting only the Locutus results, because the others don’t hold much extra interest. Locutus plays a wider range of openings than the others (perhaps because newer bots have to restrict their scope). CSE in particular is more in the do-one-thing-well camp. Besides, all of them had high win rates against lower-ranked opponents; they did not have much to learn. I don’t see a point in piling up data about similar players.

But if people want, I can post them all. Any requests?

Locutus is the only Locutusoid to use pre-learned data. Some of the others had their own ways of preparing for known opponents. For example, CSE is configured with several enemy-specific strategies, such as DT drop against #9 Iron.

Here is a summary of the pre-learned data used by Locutus. Locutus is configured to retain at most 200 game records per opponent, so that’s as much pre-learned data as it makes sense to give it. When you give it that much, each tournament game record added at the end causes one pre-learned record to scroll off the beginning. At the end of a 100 round tournament, half the game records are retained from the pre-learned data and half are tournament games—the pre-learned data more or less dominated tournament data for decisions during the tournament.

#	opponent	games	wins
7	DaQin	35	91%
9	Iron	200	93%
10	ZZZKBot	200	76%
14	Tyr	200	96%
17	Arrakhammer	200	88%
19	UAlbertaBot	71	100%
22	AIUR	51	96%
25	AILien	200	96%

Here is the final data. For every opponent that has pre-learned data, much or all of the per-learned data is retained until the end.

Locutus only recorded 8 games. It is configured to retain 200 game records, and I read the source code and verified that Locutus does not intentionally drop game records before the limit of 200. Recording exactly 8 games is the same problem that McRave suffered, and must be due to CIG problems. I don't know what the underlying problem was. My suspicion is that CIG organizers or tournament software may have accidentally or mistakenly cleared learning data for some bots. If that is what happened, and it happened once 8 games before the end of the tournament, it seems likely that it happened more than once. Who knows, though? The error might be somewhere else. Maybe they mistakenly shipped us data from after round 8 instead of round 125—in that case the tournament may have run normally, and only the data about it is wrong.

Locutus has prepared data for some opponents, stored in the AI directory. When Locutus finds it has no game records for a given opponent, it looks in AI to see if it has prepared data, and if so, it reads in those game records. At the end of the game, it writes out the prepared game records along with the record for the newly played game, and from then on the prepared records are treated like any others and retained unless and until the 200 record limit is passed.

How many other bots were affected by the 8 game problem?

---

Here is Locutus’s prepared data. Against some opponents, like McRave, Locutus picks out openings to avoid at first. If other openings don’t win either, I’m sure Locutus will come back and try these anyway. Against others, it picks out winners to try first. For some, it simply provides data. Most but not all of the prepared data is for opponents which were carried over from last year, for which pre-learning is sure to be helpful... if it is done on the same maps.

#3 mcrave

opening	games	wins
12Nexus5ZealotFECannons	1	0%
Turtle	1	0%
2 openings	2	0%

#6 iron

opening	games	wins
DTDrop	14	100%
1 openings	14	100%

#7 zzzkbot

opening	games	wins
ForgeExpand5GateGoon	2	100%
1 openings	2	100%

#11 ualbertabot

opening	games	wins
4GateGoon	1	0%
9-9GateDefensive	2	50%
ForgeExpand5GateGoon	15	93%
3 openings	18	83%

#14 aiur

opening	games	wins
4GateGoon	3	100%
9-9GateDefensive	1	100%
2 openings	4	100%

#16 ziabot

opening	games	wins
9-9GateDefensive	1	0%
ForgeExpand5GateGoon	1	100%
2 openings	2	50%

#19 terranuab

opening	games	wins
DTDrop	10	100%
1 openings	10	100%

#21 opprimobot

opening	games	wins
DTDrop	11	100%
1 openings	11	100%

#22 sling

opening	games	wins
ForgeExpand5GateGoon	2	100%
1 openings	2	100%

#23 srbotone

opening	games	wins
DTDrop	7	100%
PlasmaProxy2Gate	1	100%
2 openings	8	100%

#24 bonjwa

opening	games	wins
DTDrop	6	100%
PlasmaProxy2Gate	1	100%
2 openings	7	100%

overall

	total		PvT		PvP		PvZ		PvR
opening	games	wins	games	wins	games	wins	games	wins	games	wins
12Nexus5ZealotFECannons	1	0%			1	0%
4GateGoon	4	75%			3	100%			1	0%
9-9GateDefensive	4	50%			1	100%	1	0%	2	50%
DTDrop	48	100%	48	100%
ForgeExpand5GateGoon	20	95%					5	100%	15	93%
PlasmaProxy2Gate	2	100%	2	100%
Turtle	1	0%			1	0%
total	80	92%	50	100%	6	67%	6	83%	18	83%
openings played	7		2		4		2		3

---

Here is Locutus’s learned data. In every case, the number of games recorded is 8 plus the number of games in the prepared data. With only 8 games there is not much to go on, but the prepared data does seem to have helped Locutus choose successful openings.

#2 purplewave

opening	games	wins
12Nexus5ZealotFECannons	1	0%
4GateGoon	1	0%
9-9GateDefensive	5	80%
Proxy9-9Gate	1	0%
4 openings	8	50%

#3 mcrave

opening	games	wins
12Nexus5ZealotFECannons	1	0%
4GateGoon	3	67%
Proxy9-9Gate	5	100%
Turtle	1	0%
4 openings	10	70%

#4 tscmoo

opening	games	wins
4GateGoon	1	0%
9-9GateDefensive	1	0%
ForgeExpand5GateGoon	4	25%
Proxy9-9Gate	2	50%
4 openings	8	25%

#5 isamind

opening	games	wins
4GateGoon	6	83%
9-9GateDefensive	1	100%
Proxy9-9Gate	1	100%
3 openings	8	88%

#6 iron

opening	games	wins
DTDrop	22	95%
1 openings	22	95%

#7 zzzkbot

opening	games	wins
ForgeExpand5GateGoon	7	86%
ForgeExpandSpeedlots	2	50%
Proxy9-9Gate	1	0%
3 openings	10	70%

#8 microwave

opening	games	wins
ForgeExpand5GateGoon	8	100%
1 openings	8	100%

#9 letabot

opening	games	wins
DTDrop	8	88%
1 openings	8	88%

#10 megabot

opening	games	wins
4GateGoon	8	100%
1 openings	8	100%

#11 ualbertabot

opening	games	wins
4GateGoon	1	0%
9-9GateDefensive	2	50%
ForgeExpand5GateGoon	23	91%
3 openings	26	85%

#12 tyr

opening	games	wins
4GateGoon	8	100%
1 openings	8	100%

#13 ecgberht

opening	games	wins
DTDrop	8	88%
1 openings	8	88%

#14 aiur

opening	games	wins
12Nexus5ZealotFECannons	1	0%
2GateDTExpo	1	100%
4GateGoon	5	80%
9-9GateDefensive	1	100%
Proxy9-9Gate	4	75%
5 openings	12	75%

#15 titaniron

opening	games	wins
DTDrop	8	100%
1 openings	8	100%

#16 ziabot

opening	games	wins
9-9GateDefensive	1	0%
ForgeExpand5GateGoon	6	83%
ForgeExpandSpeedlots	2	50%
Proxy9-9Gate	1	100%
4 openings	10	70%

#17 steamhammer

opening	games	wins
ForgeExpand5GateGoon	8	100%
1 openings	8	100%

#18 overkill

opening	games	wins
ForgeExpand5GateGoon	8	100%
1 openings	8	100%

#19 terranuab

opening	games	wins
DTDrop	18	100%
1 openings	18	100%

#20 cunybot

opening	games	wins
ForgeExpand5GateGoon	8	100%
1 openings	8	100%

#21 opprimobot

opening	games	wins
DTDrop	19	100%
1 openings	19	100%

#22 sling

opening	games	wins
ForgeExpand5GateGoon	10	100%
1 openings	10	100%

#23 srbotone

opening	games	wins
DTDrop	15	100%
PlasmaProxy2Gate	1	100%
2 openings	16	100%

#24 bonjwa

opening	games	wins
DTDrop	14	100%
PlasmaProxy2Gate	1	100%
2 openings	15	100%

#25 stormbreaker

opening	games	wins
ForgeExpand5GateGoon	8	100%
1 openings	8	100%

#26 korean

opening	games	wins
ForgeExpand5GateGoon	8	100%
1 openings	8	100%

#27 salsa

opening	games	wins
ForgeExpand5GateGoon	8	100%
1 openings	8	100%

overall

	total		PvT		PvP		PvZ		PvR
opening	games	wins	games	wins	games	wins	games	wins	games	wins
12Nexus5ZealotFECannons	3	0%			3	0%
2GateDTExpo	1	100%			1	100%
4GateGoon	33	82%			31	87%			2	0%
9-9GateDefensive	11	64%			7	86%	1	0%	3	33%
DTDrop	112	97%	112	97%
ForgeExpand5GateGoon	106	93%					79	97%	27	81%
ForgeExpandSpeedlots	4	50%					4	50%
PlasmaProxy2Gate	2	100%	2	100%
Proxy9-9Gate	15	73%			11	82%	2	50%	2	50%
Turtle	1	0%			1	0%
total	288	90%	114	97%	54	80%	86	93%	34	71%
openings played	10		2		6		4		4

2 recent events with a connection to Krasi0.

Krasi0 updated

Krasi0 has been updated with terran wall skills. Locutus doesn’t understand the wall, and Krasi0 is winning against Locutus again. Bruce predicted it would happen before AIIDE, and here it is. With a wall, Locutus cannot run by into the terran main, and Locutus does not have the skills to pressure the wall.

I think Krasi0’s wall build versus Locutus leaves protoss with an advantage, because the terran natural is delayed. But Locutus, showing its Steamhammer heritage, is impatient and presses too hard early, falling behind. Krasi0 has been winning most games easily.

I’m sure that in time we’ll see a Locutus version addressing the weaknesses. For now, the elo ratings of the 2 bots are converging. Will Krasi0 be able to pass Locutus in elo? Even with wins head-to-head, that might be hard.

Steamhammer strange crash

Here’s a new one. In Krasi0-Steamhammer on Icarus, Steamhammer lost its main and natural and was left with only its third. It’s a situation Steamhammer has been in many times, and zerg normally recovers if given time. It can win the game if the opponent never finds the base, or is also crippled.

This time something went wrong that I’ve never seen: Steamhammer rebuilt drones up to 14, which is abnormal. It is coded to replace the spawning pool at 9 drones. Then, even stranger, with an idle drone because there were too many and its minerals piling up, it got into a loop where it made nothing but overlords. It seemed to be in Plato’s cave, watching a bad movie that had nothing to do with the game.

Then it crashed. Some data structure must have broken. :-(

updated Proxy

New bot Proxy is—I can almost add “of course”—updated already. The obvious change is a zergling build if the opponent is zerg; the hydralisk build was too slow for ZvZ. The zergling build is successful, and Proxy’s elo has climbed over 2000. It is now an average bot, maybe better than average. That is excellent for a newcomer.

Locutus and minimum tank range

When Locutus runs dragoons by Krasi0’s bunker, Krasi0 (in games I’ve seen by the current version) has 1 siege tank available as its main interior defense. Terran sieges the tank and Locutus loses its dragoons, doing less damage than it should.

In a broad sense, this is why I haven’t implemented runby in Steamhammer. Running by fixed defenses is easy, but playing well after you have run by is not so easy. The runby units become desperadoes, expecting to die and seeking to deal as much destruction and distraction as possible until then. Steamhammer’s units normally retreat from too much danger; desperadoes may be able to retreat, but can’t count on it. They have to make different decisions about what to shoot at, when to run away, and where to run to.

In this case, the important thing to shoot at is the tank, which limits the dragoons’ freedom too much. The dragoons should rush inside the sieged tank’s minimum range. They’ll win the fight and live to cause more trouble. Dragoons that wander too far off or take potshots at SCVs are not contributing as much as they could.

I think it’s complicated to handle all the defenses terran might try. I guess it’s a matter of taking one step at a time.

Locutus is doing great. What I find more interesting is that Microwave is also doing great since its update yesterday. In particular, Microwave seems to have improved enough to beat Iron consistently. I thought the most interesting game was the most recent one.

Furthermore, Microwave played more than one opening against Iron in its recent winning streak. Its favorite, though, seems to be 9 pool with a fast 2nd hatchery. The game plan has not changed much, only the execution is improved. Early zerglings hammer on the terran wall, occasionally breaking it down but usually only sapping the terran income. The lings don’t care if the wall is open, or if they come under fire, they only want to hit those supply depots. Microwave defends against the vulture runby with sunkens up front plus a sunken in the main. Iron usually appears surprised by the sunken in the main and fails to cope with it. Microwave follows up with hydralisks and later mutalisks, switching flexibly between hydras and mutas and preventing Iron from gathering its forces—especially targeting tanks so that they don’t build up to large numbers. Eventually Microwave reaches a critical mass of hydras and wins.

Even if you are as good as Iron, that is what happens if you always play the same and don’t update for a long time.

Locutus and Microwave are both Steamhammer forks. I’m pleased that they’re doing well. I see it as partly my success, too.

Bot authors do a lot of creative stuff. Sometimes they are so creative that I can’t figure out the idea. Like this game between Locutus and Iron: Why did Locutus’s scout probe build pylons all over Iron’s territory?

It’s not a bug. It’s an intentional feature in this version of Locutus—here is the commit. It’s called “pylon harassment” and in this version it is hardcoded to happen only against Iron. A comment says:

    // We want to build a pylon. Do so when:
    // - We have enough resources
    // - We are not close to the enemy mineral line
    // - We are in sight range of an enemy building
    // - Nothing is in the way

“In sight range of an enemy building.” The pylons are meant to be seen. The intention must be to direct the opponent’s attention, to somehow divert it from doing something Locutus doesn’t want it to do, such as leave its base and attack Locutus.

In this game, Iron was not diverted at all, and won easily since Locutus had wasted a ton of minerals on pylons. I can imagine that some bots would go wrong. Those that pull workers to defend against proxy buildings might pull too many workers and stop mining, for example. Still, if your bot does make a mistake like that, it shouldn’t be hard to fix. So if pylon harassment is useful at all, I guess it must be a trick to easily defeat some weaker bots, or bots which make a certain class of blunder and are not being updated. Or possibly it is an unfinished feature, and the way it worked in this game is not how it is intended to work. I like the second theory better.

Another comment says

    // In the future, recognize how opponents react to pylon harass and store it in the opponent model

So in its final state, it is not intended to be hand-configured, but automatically selected. It could use code similar to the auto gas steal code already in Steamhammer, which decides whether to steal gas. Or it might use code similar to the plan recognizer to decide whether the opponent made a sensible or a silly reaction, and repeat if the opponent was silly.

I like the new protoss bot Locutus by Bruce Nielsen. It is a Steamhammer fork which uses BWEB for building placement. That means it includes BWEM, which BWEB depends on, though I don’t notice any use of BWEM for pathfinding. (If it used BWEM for pathfinding, probes would not have gotten stuck behind a mineral block in this game against Bereaver.) It also has some good extensions to Steamhammer.

Locutus has a favorite build order that it uses against all races, a forge expand build that was originally designed for use against zerg. It uses BWEB to place a reasonably good wall with forge, cannons, and gateway in front of the natural, not a wall that is optimized for the terrain but one that is about as good as the walls of other protoss bots. As a new bot, it has little ability to adapt its unit mix to the situation, so it follows up with universal units, dragoons. Like Steamhammer, it eventually adds reavers and observers and a few dark templar. The dragoon micro inherited from UAlbertaBot is one of Steamhammer’s best skills, so that’s another reason dragoons are a good choice.

Locutus does know other build orders, and uses certain ones against specific opponents. [Update: I misread the configuration! It does not actually play enemy-specific build orders; the feature is turned off.] It does not use Steamhammer’s opponent model.

The forge expand build was designed for zerg opponents, but in bot world it works well against other races too. Locutus has wins over strong opponents like Bereaver and TyrProtoss. Building cannons willy-nilly has an advantage: The cannons stop most early rushes, common bot strategies. For example, PurpleSpirit tried its SCV-marine rush and failed hard.

Also visible in the PurpleSpirit game is Locutus’s changed probe micro. Probes come to defend the wall when necessary, a critical skill that Steamhammer does not have. Unfortunately, they also come to defend when it is not necessary, and Locutus tends to send too many probes and delay mining too much. Sometimes Locutus pulls probes into the middle of the map and loses them for no apparent reason.

Locutus appears to still be using BOSS for production, because it adds more gateways than it can keep busy, a typical BOSS misbehavior. But Locutus has good macro, so if so, it is using BOSS more carefully than Steamhammer (I’m going to dump BOSS so I don’t care about using BOSS carefully). Locutus can almost keep up with BananaBrain in macro, which points to good skill.

Using BWEB for building placement means that buildings are laid our more nicely than in Steamhammer. Locutus’s base is more pleasant to look at and fits more buildings. It is still possible for dragoons to get trapped between buildings, though. It may be a bug in BWEB, or in Locutus’s use of it. The 2 dragoons on the left in the picture cannot get out.

Locutus retains Steamhammer’s recon squad that performs reconnaissance in force. It’s usually good at finding and knocking down undefended expansions. Locutus also retains Steamhammer’s inability to defend its own expansions, leaving it vulnerable to an opponent that also scouts and destroys bases.

Looking into the configuration file, I see 2 nice extensions to Steamhammer’s configuration syntax. The build order is given in the usual concrete Steamhammer way, but a new location allows it to place buildings in its wall. I may adopt the same syntax for Steamhammer itself, when I get to walls.

"pylon @ wall"

There is also new “then” syntax that lets you chain actions together. I take it to mean “then with the same probe, do this next action.” Otherwise the code will assign a new probe, causing inefficient probe movement. You can chain as many actions as you like (or at least, I see an example where Locutus chains 3 actions). I can only assume that it is smart enough to assign a new probe if the first one is lost in the middle of the chain. This is a cool idea that I didn’t think of. It only seems useful for protoss, though.

"pylon @ wall then go scout location"

or

"photon cannon @ wall then photon cannon @ wall"

Overall, Locutus is a promising new bot. It has good ideas and good execution, and it already plays well. The author’s note says that new builds are coming. As Locutus gains more skills, it could become fearsome.