URL's of interest

http://www.cs.utexas.edu/users/venus/ - Venus

fuzzy logic extensions

http://www.iit.nrc.ca/IR_public/fuzzy/

RETE Algorithm

A possible inference engine is the RETE Algorithm. The RETE Algorithm is widely recognized as by far the most efficient algorithm for the implementation of rule-based systems. It is the only algorithm whose efficiency is asymptotically independent of the number of rules. Although a number algorithms implementing production rules have been considered, based on actual, empirical evidence, the RETE Algorithm is orders of magnitude faster than all published algorithms with the exception of TREAT algorithm. RETE is usually several times faster than TREAT for small numbers of rules with RETE's performance becoming increasingly dominant as the number of rules increases.

The typical RBS has a fixed set of rules while the knowledge base changes continuously. However, it is an empirical fact that, in most RBSs, much of the knowledge base is also fairly fixed from one rule operation to the next. Although new facts arrive and old ones are removed at all times, the percentage of facts that change per unit time is generally fairly small. For this reason, the obvious implementation for an RBS architecture is very inefficient. The obvious implementation would be to keep a list of the rules and continuously cycle through the list, checking each one's left-hand-side (LHS) against the knowledge base and executing the right-hand-side (RHS) of any rules that apply. This is inefficient because most of the tests made on each cycle will have the same results as on the previous iteration. However, since the knowledge base is stable, most of the tests will be repeated. You might call this the rules finding facts approach and its computational complexity is exponential