I made an OOS vs IS test (update)

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Imperial Good
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Re: I made an OOS vs IS test (update)

Post by Imperial Good » Wed, 2. Dec 20, 22:32

Killjaeden wrote:
Wed, 2. Dec 20, 18:30
Facing of the target is irrelevant for dogfights at large time scale, because it changes so fast that its no longer relevant OOS.
I think it is quite relevant so as to factor in ships trying to flee.
Killjaeden wrote:
Wed, 2. Dec 20, 18:30
Range to target is relevant, yes. Doesnt matter what the coordinates of the vector are, because there is no gravity / bullet drop to consider. And most stuff in X4 plays out on a 2D plane anyway... (unfortunate for variety, fortunate for system simplifications).
It is very much relevant since guns can only shoot forward and turrets have limited fire arcs. The current simulation factors this in but in quartiles. This is so that ships with poor rear turret coverage are less effective against targets behind them than when in front. The behaviour of attacking from behind has to be considered.
Killjaeden wrote:
Wed, 2. Dec 20, 18:30
A detailed ship shape other than general dimensions (average surface area) would be ridiculous to include in low detail simulation.
But is needed since it plays an important part of in sector combat. Something like a Xenon I is a huge bullet sponge, assuming the turret targeting is working.
Killjaeden wrote:
Wed, 2. Dec 20, 18:30
Pilot faction ? lol... since when do certain races hit better? The NN isnt supposed to tell what the ship should do either. The NN is just the formula for hit chance and practical DPS.
The combat maneuvers used depend on pilot race and skill. Without proof that this has no influence on combat results near the player it would need to be considered. This has been the case since X4 released.
Killjaeden wrote:
Wed, 2. Dec 20, 18:30
But apart from that, good luck guessing a formula that "just works" for all test cases - even if you have all the raw data you could think off. No matter what you guess, it wont fit all. The behaviour you want to simulate wont do you the favor of behaving linearly...
Which is why I would imagine gathering some statistical data would be the way to go. This statistical data can then be placed in discontinuous lookup tables and help resolve a good approximation without having to derive continuous functions. Unlike neural networks, the result and logic involved is transparent and so can be verifiable. These tables could even be specified on a per ship basis for more flexibility.
Gregorovitch wrote:
Wed, 2. Dec 20, 14:32
I would think AMD and Intel would be forced to follow Nvidia post haste if it worked.
AMD apparently is with their implementation of a DLSS competitor. But it still is nowhere to be seen... It might be that their new GPUs even have tensor core like hardware built into them, just developers currently have no way to utilize them efficiently currently. Intel still does not make a competitive discrete GPU, and as such it is also entirely possible that when they do theirs will come with such features. Intel is already pushing AI related things on their newer CPUs, including AVX512 extensions (proprietary to them) to help with AI related execution.

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Re: I made an OOS vs IS test (update)

Post by Killjaeden » Thu, 3. Dec 20, 00:20

Imperial Good wrote:
Wed, 2. Dec 20, 22:32
detailed ship shape >>> But is needed since it plays an important part of in sector combat. Something like a Xenon I is a huge bullet sponge, assuming the turret targeting is working.
You dont need to know that there is a 2m protrusion at the bow, and a 1m hole in the middle. You need to know how well you can hit it. And an average surface area value (which would be large on Xenon I) takes care of that well enough, or better said - chances for hitting a moving xenon I are almost 100%. If by sponge you mean "bullet occlusion" (things taking cover behind each other) - forget it.
Its not going to happen OOS. You cant expect the exact same results OOS. The whole point of OOS combat being a SIMPLIFICATION to safe performance. If you cant let go of some things you wont get a performance cost reduction...

If you would want to sample data for that, you can essentially also just dump the entire game memory of that battle into a file constantly... But you wont get any wiser from it, because its way too much to digest. Sure if a neural networks is presented with this garbage pile of unspecific data, it will take a gazillion neurons and years of cpu time to make heads or tails of it. Preliminary data selection and abstraction is absolutely required.
Imperial Good wrote:
Wed, 2. Dec 20, 22:32
Facing of the target>>>I think it is quite relevant so as to factor in ships trying to flee.
You can get fleeing state from his behaviour script, as a boolean. Dont need to check orientation for that and try to figure out if it's fleeing. And if it is fleeing, then again its not going to perform the same extreme turns as it would in a dogfight -> hitchance will be higher. So its simply a matter of "what state is this ship in" (active dogfight, or a "goto" objective, or stationary)
poor rear turret coverage are less effective
fighters do not intentionally try to stay in the rear turret coverage. They just randomly end up there or not. Thus if you pick a random turret "array" for a facing to apply his DPS, if rear is picked, damage will be automatically less, because its fewer turrets ... That is to say - treat fighters attacking a capital according to Heisenberg ;) They like electrons around the atom core, randomly here or there.
Imperial Good wrote:
Wed, 2. Dec 20, 22:32
coordinates of the vector >>>It is very much relevant since guns can only shoot forward and turrets have limited fire arcs. The current simulation factors this in but in quartiles. This is so that ships with poor rear turret coverage are less effective against targets
Chance of a fired bullet hitting is not affected by vector coordinates.
Can it fire on front weapons or not is irrelevant for maneuverable objects. Fighters, they turn fast enough, that you can assume they will eventually (after attack run manuever) have firing solution for x amount of seconds. That means you can get a statistical average time it takes to get one attack run, (while in dogfighting range obviously) on a specific target type (large slow vs small nimble is not the same).
lookup tables
Statistical data being required, that we can all agree. Cant simulate/aproximate something properly if you dont understand it.
However, your suggestion that lookup tables would be possible or transparent... ehh again, are you forgetting what you brought up yourself?
10 independant parameters that all affect the result (nonlinearly) lead to a 10-dimensional matrix. The amount of memory required could be quite silly, and the table lookup having to sift through large matrices and perform 10-dimensional interpolation might not be faster than having a trained NN of low complexity calculate a result.
And idk what multidimensional beeing you are, but the best i can achieve is visually process a 3 dimensional matrix, with momentary glimpses into a 4th one (3Dimensions changing over time)... a 10 dimensional matrix is far from transparent to comprehend for ordinary humans... and in a previous reply you said how many things one shall need in your opinion to consider in addition to what i mentioned below the OP - so for your standards, it might be approaching a 30 dimensional matrix or higher.
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