Hmm. Anyone have any suggestions for good primers on knowledge representation? I have a relatively complicated web of knowledge I want to write up for my games procedural generators and feel my current methods leave something to be desired. :/
I don't have a lot of recommendations because I'm still feeling my way around a similar problem. (Adventure games with semi-smart AI agents). I've resorted to Prolog, but it's not quite ideal.
You might find JSON is acceptable for small sets of data - worst case, you can probably just shove stuff in a big old array if it won't fit in an object.
Longterm, I think Lisp/Scheme is the most flexible for weird data sets, but it's hard to use.
Would love to know what works for you!
@natecull @Angle
If your data is sufficiently general-purpose / matches well with reality, there are some data sets that might be able to fill in gaps.
OpenCYC is a project where, since the early 80s, a team of people have been writing an ontology for "common sense" in a scheme dialect. They're not done.
http://github.com/dariusk/corpora has some data sets that are more specific.
@Angle @natecull
You're still going to be stuck listing these associations.
The benefit of Prolog, Lisp, and RDF is that you can use an off-the-shelf planner to navigate the associations and produce reasonable results.
The benefit of tracery is the above plus it's pretty compact (since it's json), but on the other hand you don't have backtracking.