I received notice of a Victorian government position offering $106k, as follows, today:
BRMS Developer (WebSphere ILOG JRules)
You will have proven experience as a BRMS Developer within a Java/JEE environment using IBM‘s WebSphere ILOG JRules platform. You will have implementation experience using integration technologies (e.g. Web Services, JMS) and have the ability to liaise with and engage key stakeholders. Ideally you will also have knowledge and/or exposure to IBM‘s WebSphere integration suite (including the MQ Series).
This got a reaction out of me since we’re looking for people (although emphasizing logic, semantics, and English rather than any particular engine). At first, I thought it must be a Java job, but stakeholder engagement indicates this is a full-fledged knowledge engineering position.
$100k for anyone with strong, specific experience seems low. For someone that can understand objectives and translate requirements into operational business logic, it seems lower.
I’m surprised there isn’t more of an Ilog premium, too. JBoss Drools consultants can make more than this.
FICO reported 9% growth in revenues year over year.
- the bulk of revenues and all the growth was in pre-configured Decision Management applications
- FICO score revenues were half as much, w/ B2B growing as B2C (myFICO) waned
- tools revenues were less than half again as much and flat
- optimization (XPress) was up
- Blaze Advisor was down
This is in sharp contrast to the success that Ilog has enjoyed under the IBM umbrella.
Blaze Advisor doesn’t seem to make sense as a stand-alone tool any more. Applications are great, and so are combinations of BI/optimization/rules, but if the BRMS tool will survive independently it needs to find more traction, perhaps outside of Fair Isaac.
I was prompted to post this by request from Mark Proctor and Peter Lin and in response to recent comments on CEP and backward chaining on Paul Vincent’s blog (with an interesting perspective here).
I hope those interested in artificial intelligence enjoy the following paper . I wrote it while Chief Scientist of Inference Corporation. It was published in the International Joint Conference on Artificial Intelligence over twenty years ago.
The bottom line remains:
- intelligence requires logical inference and, more specifically, deduction
- deduction is not practical without a means of subgoaling and backward chaining
- subgoaling using additional rules to assert goals or other explicit approaches is impractical
- backward chaining using a data-driven rules engine requires automatic generation of declarative goals
We implemented this in Inference Corporation’s Automated Reasoning Tool (ART) in 1984. And we implemented it again at Haley a long time ago in a rules langauge we called “Eclipse” years before Java.
Regretably, to the best of my knowledge, ART is no longer available from Inference spin-off Brightware or its further spin-off, Mindbox. To the best of my knowledge, no other business rules engine or Rete Algorithm automatically subgoals, including CLIPS, JESS, TIBCO Business Events (see above), Fair Isaac’s Blaze Advisor, and Ilog Rules/JRules. After reading the paper, you may understand that the resulting lack of robust logical reasoning capabilities is one of the reasons that business rules has not matured to a robust knowledge management capability, as discussed elsewhere in this blog. Continue reading “Goals and backward chaining using the Rete Algorithm”