OpenRules Decision Manager 8.1.0 includes a special Rule Debugger that allows business users to debug their decision models while they are being executed. The debugger stops execution after executing the first selected rule and a user can analyze the current content of all decision variables to understand why certain rules were executed or skipped. After pushing “Enter” the next selected rule will be executed. A user may continue to push “Enter” until all rules are executed. Continue reading
1. Traditional rule engines (RETE-based or Sequential).
2. Constraint-based rule engines Continue reading
Nowadays rules-based business decision models are usually developed and maintained by business analysts or other subject matter experts (not by software developers). And more and more people want to make their business decision models available from cloud as operational decision services. But is it possible for non-technical people to achieve this objective? There are so many new terms and concepts to learn, that it seems doubtful for business people to handle this task. Continue reading
When our customers create business decision models, they frequently want to have an ability to debug their business rules to understand when and why their rules were executed or skipped. We provided them with the Decision Model Analyzer that partially answers these questions but does it after (!) the model has been already executed. We’ve just completed the development of a new OpenRules Rules Debugger that allows a business user to debug her/his decision models while they are being executed. Continue reading
Traditionally, the majority of decision tables list their rules in the top-to-bottom order when different rules are placed in rows. Here is an example of a typical single-hit decision table created in Excel in accordance with the OpenRules format: Continue reading
The integrated use of Machine Learning (ML) and Business Rules (BR) is one of the most practical trends in the development of modern decision-making software. OpenRules is involved in this development for more than 10 years starting with our successful ML+BR projects for IRS. Along with a general purpose Rule Learner, we also provide Rule Compressor, that uses ML to compress large decision tables to smaller ones. This recent presentation explains how it works. Continue reading