Would anyone be interested in creating an AI that plays games?

Ah! There I go displaying my ignorance.

After watching the SMK vid, I realized the SMK program can only drive (give or take) as well as the human it learns from, which makes setting new records an impossibility.

So what happens if the trial/error system used in SMW is allowed to "mutate" a fully trained SMK program? Perhaps through some sort of shared control, where the SMK program only keeps memories from high-fitness species of the trial/error program? It seems to me that if the lap times were used as a measure of "fitness," a hybrid system could achieve some interesting results.

I know nothing about actually implementing any of that, and for all I know the idea is either redundant or impossible, but I figured I'd share regardless.

[–] PMYA [OP] 1 points (+1|-0)

The criteria for the SMW AI improving is extremely basic. All it really does is try to move right as much as possible, with a small incentive to go fast. It also has no starting point to work from, it just does stuff randomly until something good happens, and then it builds from that.

In SMK, the criteria for measuring progress is infinitely more complex. It needs a starting point to go from, because letting it hit random buttons is not going to produce the same level of results as it does in a 2d platformer. There are also issues with developing long term strategies. Imagine a square track, just 4 corners. Let us assume that the AI's starting point is a path that drives all the way around the track in the middle of the road. It mutates a lap attempt where it takes Corner 1 sharply, and saves time overall, so it memorises this action for going around Corner 1. But imagine that the line it takes around Corner 1 makes it impossible to hit an optimal angle on Corner 2, and the real best way to get around the first two corners is to not take the "best" line around Corner 1 in order to get a better average time around both corners.

This example only scratches the surface at how insanely complex a racing AI would be in comparison.

[–] Sarcastaway 1 points (+1|-0)

I see what you're saying, but wouldn't using lap time as an indicator account for that? If the strategy for corner 1 left it at a disadvantage for corner 2, the overall lap time would reflect that, correct?

Either way, I totally get why brute-force trial/error works better in a 2D setting. SMW has orders of magnitude less possibilities, between directional limitations, fewer controls, and one fewer dimension of travel.

[–] PMYA [OP] 1 points (+1|-0)

wouldn't using lap time as an indicator account for that?

It would, but that theory assumes that the AI would correct what it did on the first corner and try sacrificing time there to gain it later on. This is probably not going to be the case, as it is very difficult to get an AI to think this way. It is a variant of this problem.

Would anyone be interested in creating an AI that plays games?

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