I grant both your points, but I don't think that the typical problem in game AI is _finding_ hidden relationships between variables, it's creating them!
"... that perform exactly the same function in some game, somewhere....I'd like to see...backprop neural net and adaptive planner"
A perceptron _is_ a neural net, and if I understand Evans correctly, he's not saying that the use of decision trees per se is unique (it isn't), but that the game objects use perceptrons to weight their traversal of the decision tree -- which would be an adaptive planner. B&W is the first successful game that even comes close to demonstrating "real" AI techniques.
You'd be amazed at the lack of AI sophistication that's shipped in games. As far as I know (and, just to establish some credentials, I was the founding editor of Game Developer Magazine, the editor of AI Expert magazine, and used to teach AI techniques at the Game Developer's Conference), no commercially successful game has _ever_ before shipped with an AI based on neural nets, genetic algorithms, true fuzzy logic, or even a "real" inference engine. There have been a few non-important games that have used non-adaptive neural nets and at least one almost-successful game that claimed to use GAs (Creatures? It was kind of like a Tamagotchi-- you raised these things in an environment and taught them how to catch food and so forth.)
90% of game AI is based on finite state machines, decision trees, and scripting.
In defense of game programmers, though, everyone thinks that it would be easy to "use a neural net" to control a game object. Generally not so. A neural net is a pattern-recognizer, not a symbol manipulator. Anything you can do with a neural net you can do with boolean operations, and a sequence of boolean gates is typically faster to program and execute. But what's clever about B&W, if I understand Evans correctly, is that NNs are used to weight the traversal of a pre-existing decision tree (i.e., the next time I "see" a fire burning, I am marginally more likely to cast a "Water Miracle"). That's a good design, since god games are enormously repetitive.
The other type of game object for which I've been baffled that no one has shipped a neural network is in a fighting / fast reaction game, learning the player's bias (does he always break left and then perform an immelman?, does she always use a particular fighting move?), but most introductory books on NNs don't discuss neural nets that can handle temporal data. So there are a million game programmers who know enough about NNs to "know" that they don't work.
A lot of games have also claimed to ship with fuzzy logic, but in every case that I have spoken with the developers, it turned out to be a probabilistic overlay on the results of some boolean operations, not the higher-order symbolic manipulation that characterizes "real" fuzzy logic.
The Creature behavior in B&W is brilliant. Like the classic AI program Eliza, it demonstrates how ready we are to project "intent" and "consciousness" onto computational structures that are, in reality, not very sophisticated at all.
Pfeh! "advanced armies"! The glory of this here U-S-of-A is that not only can a couple of apple-cheeked kids build an advanced electromagnetic slug-thrower, they have the Constitutional right to bear it. Now, if only we could get our hands on some depleted uranium, we'd get rid of that "The 2nd Amendment is irrelevant because the Army has tanks," argument.
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I grant both your points, but I don't think that the typical problem in game AI is _finding_ hidden relationships between variables, it's creating them!
A perceptron _is_ a neural net, and if I understand Evans correctly, he's not saying that the use of decision trees per se is unique (it isn't), but that the game objects use perceptrons to weight their traversal of the decision tree -- which would be an adaptive planner. B&W is the first successful game that even comes close to demonstrating "real" AI techniques.
You'd be amazed at the lack of AI sophistication that's shipped in games. As far as I know (and, just to establish some credentials, I was the founding editor of Game Developer Magazine, the editor of AI Expert magazine, and used to teach AI techniques at the Game Developer's Conference), no commercially successful game has _ever_ before shipped with an AI based on neural nets, genetic algorithms, true fuzzy logic, or even a "real" inference engine. There have been a few non-important games that have used non-adaptive neural nets and at least one almost-successful game that claimed to use GAs (Creatures? It was kind of like a Tamagotchi-- you raised these things in an environment and taught them how to catch food and so forth.)
90% of game AI is based on finite state machines, decision trees, and scripting.
In defense of game programmers, though, everyone thinks that it would be easy to "use a neural net" to control a game object. Generally not so. A neural net is a pattern-recognizer, not a symbol manipulator. Anything you can do with a neural net you can do with boolean operations, and a sequence of boolean gates is typically faster to program and execute. But what's clever about B&W, if I understand Evans correctly, is that NNs are used to weight the traversal of a pre-existing decision tree (i.e., the next time I "see" a fire burning, I am marginally more likely to cast a "Water Miracle"). That's a good design, since god games are enormously repetitive.
The other type of game object for which I've been baffled that no one has shipped a neural network is in a fighting / fast reaction game, learning the player's bias (does he always break left and then perform an immelman?, does she always use a particular fighting move?), but most introductory books on NNs don't discuss neural nets that can handle temporal data. So there are a million game programmers who know enough about NNs to "know" that they don't work.
A lot of games have also claimed to ship with fuzzy logic, but in every case that I have spoken with the developers, it turned out to be a probabilistic overlay on the results of some boolean operations, not the higher-order symbolic manipulation that characterizes "real" fuzzy logic.
The Creature behavior in B&W is brilliant. Like the classic AI program Eliza, it demonstrates how ready we are to project "intent" and "consciousness" onto computational structures that are, in reality, not very sophisticated at all.
Pfeh! "advanced armies"! The glory of this here U-S-of-A is that not only can a couple of apple-cheeked kids build an advanced electromagnetic slug-thrower, they have the Constitutional right to bear it. Now, if only we could get our hands on some depleted uranium, we'd get rid of that "The 2nd Amendment is irrelevant because the Army has tanks," argument.