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Zia and mutalisk micro

Zia’s mutalisk cloud is scary when it gets big. Eventually the mutas not only one-shot the units that they target, but their bounces instantly kill nearby units. The mutalisks sweep a path of destruction. But think about it—is that efficient? If mutalisk bounces at 1/3 power kill instantly, then the main attack must usually be gross overkill. Most of the firepower is wasted.

The idea of individual mutalisk control, as introduced by the Berkeley Overmind and copied by other zergs since, is to waste no firepower. Each flier independently dances in and out for safety and ideally attacks at near its maximum rate. But watch how Tscmoo zerg implements this: Its mutalisk cloud is also scary when it gets large, but usually not as scary as it could be, because it spreads out too much. Sometimes half the mutas are posing for pictures with the ground army while half are on the job. And the attackers often pick some targets over here, some over there, and don’t kill either as fast as they should. Tscmoo doesn’t focus its fire enough; it’s the opposite mistake from Zia.

Causing damage does not win games. Maximizing your damage output is not the winning move. You want to balance between killing the most important enemies and staying alive.

Try to imagine PerfectBot’s muta micro. Even PerfectBot can’t truly play perfectly, because calculating optimal micro is infeasible. But surely PerfectBot focuses fire efficiently, switching mutas fluidly between targets, taking into account importance and time to kill based on distance and damage rate and expected losses, to reduce overkill to near zero and spend less time flying between targets and strike a good balance between killing the most important stuff fast and staying alive. “This takes 5 more shots to kill, 12 are shooting, might lose 1, so switch 6 to new targets.” Zia and Tscmoo zerg are no competition for Jaedong, but I think Jaedong would boggle at PerfectBot’s mutalisks.

How close can we get to PerfectBot micro today? 1. Given a set of targets in priority order, calculating how to focus them down efficiently with minimal waste seems intricate but ultimately not that hard. 2. Folding in a desire to also minimize losses makes optimal decisions computationally infeasible. Even approximations seem tough. 3. Prioritizing the targets depends on the total game situation and will have to be done heuristically. For now I guess we’ll have to settle for a simplified algorithm.

Watching Zia last week, I thought it picked targets usually one at a time (simple 3) and once the target was chosen ignored damage taken while chasing it down (very simple 2), so the intricate-but-not-hard efficient killing calculation by itself should be a big improvement. Zia-this-week has been updated and has fancier micro than Zia-last-week, so I’m already behind the times! I got the impression that Zia-this-week is better about picking targets and switching targets and avoiding damage, but that it still wastes shots with too much overkill.

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ratiotile on :

A coordinated targeting algorithm is described in Johan Hagelback's thesis, at http://www.bth.se/tek/jhg.nsf/bilagor/JHG_Lic_Thesis_pdf/$file/JHG.Lic.Thesis.pdf

Unfortunately it doesn't appear to have made it into Opprimobot.

Jay Scott on :

Thanks! The thesis is from 2009 and it’s about using potential fields for as many RTS tasks as can be. I found the “attack coordination” algorithm starting on internal page 27, which is page 43 of the pdf (that sure is confusing).

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