This is game AI, games called this sort of thing "AI" for a long time. Behavior trees is (among others) one of the most common things someone with the role of game AI programmer will implement.

This has been the case since at least the 90s, it is not a new thing.

There are paradigms of AI that are not deep learning. If you took an AI course in the 90s or earlier, implementations like this are much closer to what you would learn about -- symbolics/GOFAI. It remains basic to some fields where stakes and complexity are high (air traffic control and military systems) but determinism is a strict requirement, not to mention others like gamedev that have lots of performance constraints -- and usually don't actually need or want anything non-deterministic or overly smart.

Deep Blue, the first chess engine to defeat a world champion, was a GOFAI system

There was an article recently about a system used in production at a pasty chain in Japan to classify pastries at checkout that didn't use DL for most of its existence. Now it seems to be a hybrid system that uses symbolics and DL for certain functions

https://www.newyorker.com/tech/annals-of-technology/the-past...

FYI, one of the most well-known books about writing game entity behavior is literally called "Programming Game AI by Example." (published in 2004)

https://www.amazon.com/Programming-Example-Wordware-Develope...

That was called AI before the current LLM-AI era. Your comment reads like someone complaining that cryptography is called crypto

> What you're describing is a behavior tree: predefined logic, predefined responses, no learning, no inference, no model.

Stop calling everything AI, guys.

Depends on how pedantic you want to get, one could argue that regular expressions are AI too.

https://www.rand.org/content/dam/rand/pubs/research_memorand...

Regexes were invented for much higher order tasks (modeling neural networks) than just making find-and-replace easier.

The logic used to implement game NPCs has been called "AI" since well before the current AI boom. And many of the techniques come from the previous AI boom of the 1970s-1980s.

I know that we're all experiencing AI fatigue, but this comment is an example of the "once an AI technology finds a niche and becomes accepted technique within that niche, it ceases to be AI" meme.

You do realize that an LLM is an enormous decision tree? The prompt is the state and output tokens added to that are the subsequent state that's fed back into the machine. Running the math without deliberately adding any randomness would produce a deterministic output.

> This isn't AI...It's a behavior tree. Calling every decision-making system "AI" is like calling a flowchart a neural network. What you're describing is a behavior tree: predefined logic, predefined responses, no learning, no inference, no model.

This is literally AI. A behavior tree is AI, all of those things are AI. It's just symbolic rather than neural network based.