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Posts Tagged ‘Fair Isaac’

Requirements for Logical Reasoning

Here is a graphic on how various reasoning technologies fit the practical requirements for reasoning discussed below: This proved surprisingly controversial during correspondence with colleagues from the Vulcan work on SILK and its evolution at http://www.coherentknowledge.com. The requirements that motivated this were the following:

Blaze down in Fair Isaac’s Q1 2012

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 [...]

Pursuing a decision tree down a rat hole

Fair Isaac’s recent press release touts the “key differentiator” of Blaze Advisor 7.0 as: the innovative Decision Graph visual metaphor, a decision tree management solution that makes even the most complex rule sets easier to manage and explain Of course, a decision tree is really more like a root system (i.e., the tree is upside [...]

Rules vs. applications of knowledge

I was just asked for some background on business rules and the major players, preferably in the form of videos. The request came in by email, so I didn’t have the opportunity to immediately ask “why”.   Below I give some specific and direct responses, but first a few thoughts about clarifying objectives. I don’t know [...]

IBM Ilog JRules for business modeling and rule authoring

If you are considering the use of any of the following business rules management systems (BRMS): IBM Ilog JRules Red Hat JBoss Rules Fair Isaac Blaze Advisor Oracle Policy Automation (i.e., Haley in Siebel, PeopleSoft, etc.) Oracle Business Rules (i.e., a derivative of JESS in Fusion) you can learn a lot by carefully examining this [...]

How is a process an event?

processes are events that take time

Goals and backward chaining using the Rete Algorithm

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 [...]