Clojure, Python, Common Lisp, are other candidate languages for AI.
I love to write, and if I could get a world class Clojure coder (perhaps someone like Alex Ott, or someone with similar skills) to co-write, it would be fun to start over.
For example Weka is widely used for data mining (even in academia) and here it's used in the Machine Learning chapter; Drools is an excellent solution from JBoss/Red Hat used in the chapter for Expert Systems, and etc... I even see a Hadoop dependency in the code but I'm not sure (yet) in which chapter it's used.
I bought the book, as a Java developer this is one of the areas I'm less experienced in, so this is a great opportunity to get up to date.
Practical AI stuff can be done in most (lower level) practical languages.
It can be done, but that does not mean that it necessarily makes sense to do so. The question is, what advantage does Java really have here, over something like Clojure?
http://www.cs.st-andrews.ac.uk/research/aisc
This is not to say that you cannot do equivalent things in Java, but it is a lot easier in Lisp.
I still have this (https://www.librarything.com/work/3032548) book somewhere. Working through it as a kid was an interesting experience (amplified by the fact my computer was an Apple II+ at the time).