I am currently dabbling in expert systems, emacs lisp, and reading up about artificial intelligence. Traditionally, artificial intelligence is associated with LISP and expert systems with CLIPS. However, I have noticed in computational sciences how much Python is being used. What about the area of artificial intelligence and machine learning? is it still been dominated by LISP? how much is python being used in AI? are any of the newer functional languages, clojure for example, being used in research?
in the area of expert systems, which shells are most used/popular today? are there any interesting developments language wise which you know of?
It depends what area of AI.
Not at all — unless it’s suddenly had a resurgence in the last few years.
People will use whatever language is appropriate for their domain. You also have to factor in the availability of libraries — if you’re doing some data mining task, you might download Weka and use Java. Or if you’re doing some agent theory research that involves sending structured XML messages, you might find yourself using whatever language your favourite XML parser is in. Or if you’re building a high-performance backgammon program, you might stick with C/C++ and use an existing evaluation function (as I did with my research using gnubackgammon).
Expert systems really aren’t so much the rage anymore. As research went along they were found to be brittle systems that need too much manual TLC. If you’re going to try and detect cancer, or qualify someone for a credit card, you’re better off using some ML system, like a Bayesian Network.
I think you’ll find most AI textbooks are fairly platform agnostic since the underlying algorithms are platform agnostic.