[MUD-Dev] NPC AI

[Travis Casey]

Brian Price <blprice at bedford.net> wrote:

[using subsumption architecture for NPC AI]

>The simple layers could be implemented by a mobprog like interpreted 
>language, but once again I noticed a similarity with another field.  
>Each layer is basically a control system with a well known problem 
>space.  (Assuming that the mud's game mechanics are simple enough to 
>qualify as well known.)  Now this will hardly be new to some of you, 
>but there exists a cross between expert systems and AI that was 
>specifically designed for control system implementation where the 
>problem space is well known, namely fuzzy logic.  

"A cross between expert systems and AI?"  I remember when expert
systems *were* AI.  What's the old AI researcher's saying?  "It
stops being considered AI as soon as it works well?"  :-)

Fuzzy logic isn't really a cross between any two things -- rather,
it's a possibly new ("possibly" because some mathematicians believe
that it's functionally identical to Bayesian logic) branch of 
mathematics which can be applied in AI systems to make it easier to
work with a reality in which things aren't always well-defined.  Thus,
there are expert systems which use fuzzy logic, neural nets which use
fuzzy logic, and other AI systems which use fuzzy logic.

>If learning capability is desired, it may well be possible to work 
>out a genetic algorithm that worked on fuzzy rule sets.  The 
>advantage as compared with neural networks would be faster execution 
>and lower memory requirements.  Of course, such a solution would not 
>be as smart or capable as a neural net especially if the problem 
>space is less than well known, or if bad assumptions are made in the 
>design of the starting fuzzy rule sets.

There's also a combination of expert systems and neural networks 
called "expert networks."  I've never looked into the details, but
the basic idea is that you take an expert system and train its rules
like you would a neural net's nodes -- strengthen those rules which
are used in successful inferences and weaken those used in 
unsuccessful inferences.  Naturally, you can use fuzzy logic in an
expert network.

>As a side note, I have read of solutions that used a mixture of 
>neural nets and fuzzy logic where neural nets provided some learning 
>capability.  Unfortunately I don't have enough expertise with AI to 
>evaluate the suitability of such a combination for muds.  Indeed I 
>don't have the necessary expertise to evaluate the combination of 
>fuzzy logic with genetic algorithms.  I'm hoping that the AI gurus in 
>this group can provide an expert opinion.

Expert networks may be what you're referring to here -- I'm not really
familiar enough with the field to know for sure.  The only reason I've
ever heard of them is because they were the field of research of a 
CS professor I worked for.

Personally, I think an expert system would be a good way to make more
intelligent NPCs -- but that's probably just because I have more 
experience with them than with other AI systems.  The main thing that
I find attractive about using an expert system for NPCs is that you
can get results quickly -- there's no training period needed, like
there is with neural networks or genetic algorithms.  Also, since you're
basically setting up rules for the NPCs to use, you can improve the rule
set over time by observing what the players do that's effective and 
adding rules that make the NPCs do the same thing.
--
      |\      _,,,---,,_        Travis S. Casey  <efindel at io.com>
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