@PlebScrubber Yeah, but can you fight with the same number of units and still end up with 5 like he did? Maybe... Let's tell him to keep evolving, but to mix this genetic code with another 5 which each have 500 generations then to mix all of them together and make a smart one.
@TimJSwan89 all it does it have many units attack the same enemy unit, so it dies very quickly, and then all target the next one, this means the total damage taken is much less and more units survive
if you left the units to act naturally, they would each just target the nearest enemy and their combined fire would be spread thin, that means enemy units will take longer to die, and have more time to deal damage to friendly troops
@ross817 Yes, most problems can't be solved with genetic algorithms. However, if you have a way to judge how good a solution is and when the problem is solved, and the factors aren't too many, it should be solveable with genetic algorithms.
Very cool. what did your chromosomes contain? the wall-hugging behavior was interesting
duzgy 2 months ago
yeah I count 9 vs 6 units, unfair...
more numbers of same unit...
PlebScrubber 9 months ago
@PlebScrubber Yeah, but can you fight with the same number of units and still end up with 5 like he did? Maybe... Let's tell him to keep evolving, but to mix this genetic code with another 5 which each have 500 generations then to mix all of them together and make a smart one.
TimJSwan89 8 months ago
@TimJSwan89 all it does it have many units attack the same enemy unit, so it dies very quickly, and then all target the next one, this means the total damage taken is much less and more units survive
if you left the units to act naturally, they would each just target the nearest enemy and their combined fire would be spread thin, that means enemy units will take longer to die, and have more time to deal damage to friendly troops
PlebScrubber 5 months ago
@PlebScrubber count again...
DizzerJoz 5 months ago
9 vs 6? Unfair...
UnrealQW 1 year ago
@UnrealQW
There were nine units on each side, but red won because three of blue's units showed up late to the fight.
tifforo1 1 year ago
@tifforo1
blue also does several actions to micro the dieing units away making red target the other higher hp unit
Talis116 11 months ago
@tifforo1
red also does several actions to micro the dieing units away making blue target the other higher hp unit
Talis116 11 months ago
so this was an evolutionary arms race with red vs blue? or was red evolving the best solution to attack blue?
777Skeptic 1 year ago
Are there any problems that can't be solved with genetic algorithms?
ross817 1 year ago
@ross817 Finding a girlfriend
hmanham 1 year ago 5
@hmanham
this problem was solved by many products of genetic algorithms
Nimmermaer 6 months ago
@ross817 Yes, most problems can't be solved with genetic algorithms. However, if you have a way to judge how good a solution is and when the problem is solved, and the factors aren't too many, it should be solveable with genetic algorithms.
alexander256 8 months ago
is this comp ai
or is this like... you program ur own units to do better in matches? xD
vipersrules 1 year ago
This is very impressive. Came from your site.
hobote 2 years ago
Very cool! How many generations did it take to come up with this solution?
MiniAgupa 2 years ago
@MiniAgupa This was generation 638. Similar solutions started to emerge after ~400.
AntiRushx2 2 years ago
@AntiRushx2 Can you provide your compiled AI ? I wanna play vs it.
I have a cpu than run day and night if you want to let it learn an infinite number of time
@FusionNinjin in c++, using bwapi
mamelouk69 2 years ago
nifty, but i think a better question is how you can program untop of starcraft :S
FusionNinjin 2 years ago
how does your algorithm work ?
igoronline 2 years ago
@igoronline
Like the title says: Genetic Programming. The agents genetically inherit the traits that maximize their fitness (survival).
ozpowermo 1 year ago