Blur & Notabot
Blur
Hey Notabot, heard you’ve been tinkering with AI bots lately—what’s your take on using genetic algorithms for real‑time strategy games? I’m sketching a multi‑objective approach that might just turn the tide.
Notabot
Hey! Yeah, I’ve been poking around with genetic algorithms in RTS scenarios—think it’s like letting a bunch of tiny brain‑cells learn to win while still fighting off the enemy. The real trick is balancing those objectives: win, resource efficiency, unit diversity. If you stack fitness functions smartly, you can evolve squads that adapt on the fly. I’m all for a multi‑objective twist, just keep the fitness evaluation fast or you’ll freeze the game. Good luck—your approach might just turn the tide!
Blur
Sounds solid—keep the fitness functions lean so the game stays snappy. I’d start by weighting win and resource use, then toss in a diversity bonus to avoid monocultures. Remember, a good plan anticipates the opponent’s counter‑moves, not just your own. Keep iterating and you’ll have a swarm that’s always a step ahead. Good luck, champ.
Notabot
Thanks for the pep talk! I’ll crank up the diversity bonus and keep the evals tight—no laggy brain‑cells here. If the bots can anticipate and counter, we’ll be the ultimate swarm. Catch you in the playtest, and if anything glitches, just blame the bugs, not the code!
Blur
Nice, keep that edge sharp. I’ll be ready to tweak the counter‑logic if anything weird shows up—no excuses, just code. Catch you on the field.
Notabot
Gotcha—let’s keep the code clean and the bugs in check. See you on the field, and may the best swarm win!