Fuzzy logic is a vary useful non boolean logic system. http://en.wikipedia.org/wiki/Fuzzy_logic In practice it's somewhat like neural net's but in a far more human readable format and vary useful for things like washing machines that have lot's of flakey sensors and little processing power. But the basic idea is statements truth is percentage based. For example "this statement is true" would be 50% true and there is no contradiction.
PS: Yet another 1960's discovery that keeps being renamed and rediscovered.
Do you have personal, real-world examples of fuzzy logic being useful to you? I find Bayesian statistics useful regularly; fuzzy logic not so much. What am I missing?
The tradeoff between accuracy and speed. Real world devices ofen have tight feedback loops and flakey sensors so you need something that aproximates Bayesian logic without being bogged down.
The only real world example I have Persionaly used was a controller for a hacked together hot tub, the basic problem was generally adapting a simple program concept to both limited processing power and flakey data. You want to write if temperature is > value instead you go if 70% sensors in area x say temperature > value. You could try to find a better aproximation but the more you calculate the longer it is until you can process more data. We also had ~380 bytes of RAM and 2000 bytes for sorce code so things needed to be simple.
Sure, you could try and find the actual energy in the hot tub water but that's not needed, you really just want to know if the heater is on for to long with the pump off then shutdown for safety otherwise shutdown if temperature is probably to hot.
PS: Yet another 1960's discovery that keeps being renamed and rediscovered.