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[img]https://serving.photos.photobox.com/51084974ed15d8bc19dd0330bc709e240c63f94ab275f56136dc71feb6f6860bfef60f2f.jpg[/img]
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[img]https://serving.photos.photobox.com/51084974ed15d8bc19dd0330bc709e240c63f94ab275f56136dc71feb6f6860bfef60f2f.jpg[/img]
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Update: just a prototype; Velocity is max speed, Agility takes into account dynamics such as acceleration and turn rate. Accuracy is arbitrary number accounting area of effect and weapon type (homing or not, hitscan etc.)
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Update: just a prototype; Velocity is max speed, Agility takes into account dynamics such as acceleration and turn rate. Accuracy is arbitrary number accounting area of effect and weapon type (homing or not, hitscan etc.)
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I might add some additional values like suggested:
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I might add some additional values like suggested:
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- strength
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- strength
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- alpha dmg
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- alpha dmg
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And remove some:
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And remove some:
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- hp in favor of hp/cost
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- hp in favor of hp/cost
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... etc.
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... etc.
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I'm open to suggestions, now that I have the tool to generate those graphs quickly I'd probably make a screen with class-general values and for all units individually in said class.
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I'm open to suggestions, now that I have the tool to generate those graphs quickly I'd probably make a screen with class-general values and for all units individually in said class.
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The colors and design will probably change. I can also try to check accuracy of k-nn classification with these averaged datapoints as anarchid suggested to see how they hold up.
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The colors and design will probably change. I can also try to check accuracy of k-nn classification with these averaged datapoints as anarchid suggested to see how they hold up.
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Also I'll probably make instead arbirtary 5-scale make a ranking among classes in the next iteration.
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