TREAT: a new and efficient match algorithm for AI production systems
TREAT: a new and efficient match algorithm for AI production systems
Logical foundations of object-oriented and frame-based languages
Journal of the ACM (JACM)
Production matching for large learning systems
Production matching for large learning systems
Access to Objects by Path Expressions and Rules
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
The LEAPS Algorithm
A non-monotonic expressiveness extension on the semantic web rule language
Journal of Web Engineering
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The evaluation of production rules is typically based on the Rete-algorithm. The topic of the current paper is to investigate, whether set-oriented bottom-up evaluation of rules in deductive databases can also take advantage of the Rete approach. We report on our implementation of the Rete algorithm as one possible evaluation technique inside the F-Logic rule evaluation engine Florid. We demonstrate, that in situations in which several rules share common subgoals a considerable improvement of the execution time can be gained by the Rete approach. We show this by means of benchmark programs, also comparing our results with the performance of Jess, a production rule system relying on Rete.