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I had the same reaction. Almost nothing but FSMs in game AI. Makes me wonder if we need to look beyond FSMs for the next level of intelligence.



About 10 years ago when I was reading a lot about AI game dev I remember reading about Fuzzy State Machines ( http://www.coniserver.net/wiki/index.php/FuSM ) which were seen as an improvement from classical FSM.

I think I read it in one of the "AI programming Gems" books.


Going by the name, those are based on Fuzzy Logic, I assume - which makes sense. Some people say that the first nation to develop a true AI will be Japan, because they've been studying Fuzzy Logic theory as a field of science since decades.


The natural next step is a PDA. Perhaps you could use this type of system to model an AI that can get distracted or become faced with an intermediate task and then return later to the original objective?


For those of you who don't know what a PDA (Push Down Automaton) is, it is basically a standard finite automaton but with a stack that you can push things to and pop things of -- you can then react differently if you get input a in state B versus getting input a in state Q.

Many parsers make use of PDAs when they parse source code.


I've used PDA in games A.I. programming several times too. In fact I'd be surprised to see anything beyond a casual game that didn't use high level 'task stacks'.


We use hierarchical state machines (i.e. statecharts) quite a bit in our games.


It's fairly common these days to use something beyond FSMs, e.g. simple planning (whether classical or hierarchical), or hierarchical behavior trees. In other cases, more emergent "smart world" type methods, like influence maps or smart-objects.




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