I'm developing an action rpg with some University colleagues. We've gotton to the monsters' AI design and we would like to implement a sort of "utility-based AI" so we have a "thinker" that assigns a numeric value on all the monster's decisions and we choose the highest (or the most appropriate, depending on monster's iq) and assign it in the monster's collection of decisions (like a goal-driven design pattern) .

One solution we found is to write a mathematical formula for each decision, with all the important parameters for evaluation (so for a spell-decision we might have mp,distance from player, player's hp etc). This formula also has coefficients representing some of monster's behaviour (in this way we can alterate formulas by changing coefficients).

I've also read how "fuzzy logic" works; I was fascinated by it and by the many ways of expansion it has. I was wondering how we could use this technique to give our AI more semplicity, as in create evaluations with fuzzy rules such as
IF player_far AND mp_high AND hp_high THEN very_Desiderable
(for a spell having an high casting-time and consume high mp) and then 'defuzz' it. In this way it's also simple to create a monster behaviour by creating ad-hoc rules for every monster's IQ category.

But is it correct using fuzzy logic in a game with many parameters like an rpg? Is there a way of merging these two techniques?
Are there better AI design techniques for evaluating monster's chooses?