[_delirium]

It's used somewhat in AI still, especially the communities going under the name "computational intelligence" (CI). In many communities it's been supplanted by various statistical approaches, though. Fuzzy logic starts from logic, and adds in non-binary distinctions. An alternate approach is to start from statistics, and add in structure: things like Markov logic networks, Bayesian graphical models, probabilistic planning, hierarchical reinforcement learning, and a dozen other such approaches. Both sets of approaches have the same high-level goal of bringing together symbolic reasoning with numerical inference, in some form.

The second basket of approaches (statistics+structure) is now more popular overall than fuzzy logic I think, though it depends on what communities you're from; fuzzy logic is much more popular in engineering-flavored disciplines than in math-flavored disciplines.

[probably]

Great summary of the situation -- did not expect. Thanks!