I had the same experience. I was creating a multi-user game-like experience and I had to come up with a client-side human "simulator" that was meant to be used if human players couldn't be found (what people would call a "bot" in most games). I tried several different iterations of what I perceived to be complex human-like decision-making rules. In the end what I ended up using was just very simple behavior mostly based on random number generation. Users could not distinguish that from real people. My previous complex rules-based solutions felt very robotic in comparison.
Still, I consider the classic game AI to be a real type of AI. They're just different things when compared to things like Machine Learning. Despite (and your) my example, most of the time, when creating game AI you have to distill the rationale a player would have to a set of rules, and then build it from the ground up as a rudimentary intelligence that can make decisions. Sure, there's "shallower" games, but also games that distinguish themselves when good AI is in place. I keep thinking of the AI in Quake 1 bots, and when a game like S.T.A.L.K.E.R. had good opponents. It was refreshing.
I'd even say there's some beauty in it, especially when you get to some emergent behavior that you did not expect.
I think Machine Learning is all the rage today mostly because you can attack a problem using brute force, without having to understand what drives a behavior. It may be more human-like, but to me it's just a separate branch.
Still, I consider the classic game AI to be a real type of AI. They're just different things when compared to things like Machine Learning. Despite (and your) my example, most of the time, when creating game AI you have to distill the rationale a player would have to a set of rules, and then build it from the ground up as a rudimentary intelligence that can make decisions. Sure, there's "shallower" games, but also games that distinguish themselves when good AI is in place. I keep thinking of the AI in Quake 1 bots, and when a game like S.T.A.L.K.E.R. had good opponents. It was refreshing.
I'd even say there's some beauty in it, especially when you get to some emergent behavior that you did not expect.
I think Machine Learning is all the rage today mostly because you can attack a problem using brute force, without having to understand what drives a behavior. It may be more human-like, but to me it's just a separate branch.