Identification of the Executed Rules

Our customers often want to identify  the actually executed rules. By default they may look at the automatically generated execution reports in the HTML format Continue reading

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Predictive Analytics is Becoming Mainstream

“Big Data” have brought “Predictive Analytics” (long-time available but hidden in the academic world under the names “Machine Learning” and “Data Mining”) to the spotlight of the modern Business Analytics. These days you will find many examples when analytics enables business decisions by supporting a path from data to decisions and actions. Below I will briefly talk about nowadays positioning of the Business Analytics and more about OpenRules own experience in this area including OpenRules Rule Learner. Continue reading

Don’t Program a System, Educate It!

Modern decision management techniques enable business decisions by supporting a path from data to decisions and actions. Wherever people use stand-alone Business Rules, Complex Event Processing, Predictive Analytics, Optimization systems or their combinations, they prefer to put in charge subject matter experts and not software developers.  Actually, all these systems tend to be declarative and allow customers to feed their systems with externally maintained business knowledge, e.g. historical data and/or already known business rules. Nowadays people in a way want to educate a general purpose system with their domain-specific knowledge avoiding traditional programming. Continue reading

DMN 1.1 Issues: Aggregation

DMN defines “aggregation” in the following way:

“Multiple hits must be aggregated into a single result. DMN 1.0 specifies six aggregation indicators, namely: collect, sum, min, max, average. Optionally, the aggregation indicator may be included in the table. The default is collect.”

Below is a list of my issues with this DMN 1.0 approach. Continue reading

Decision Model “Vehicle Insurance – UServ Product Derby”

As a response to the DMCommunity.org challenge, I will describe an OpenRules-based implementation of the highly popular use case known as “UServ Product Derby”. The use case deals with automobile insurance problems including eligibility and pricing decisions for a hypothetical insurance company “UServ”. Its detailed description can be found here. Our implementation may be considered as another complex-enough example of the DMN approach. Continue reading

Decisions with Mitigation Criteria

The Decision Management Community (http://DMCommunity.org) published an interesting Challenge in Oct-2014. It deals with a quite typical problem when some business rules may be mitigated by other rules.  Here is an OpenRules-based solution that follows the DMN guidelines. The main idea is to use multi-hit decision tables when more specific rules (mitigations) may override more generic rules. Continue reading

Learning Business Rules from Data at RuleML-2014

This year RuleML-2014 will be held in Prague on Aug 18-20. For the first time it will include a special track called “Learning Business Rules from Data”.  As a member of the organizing committee, I posted the proper announcement here. It promises to become a very interesting event when the decision management practitioners meet their academic partners. Continue reading

Can a Decision Model Define Uniqueness of Objects inside a Collection?

This question was asked by Antonio Plais – see the LinkedIn discussion. Several practical variations of this question were mentioned: 1) Define if the same product appears more than once in the same sales order; 2) determine the uniqueness of records in a file to be loaded into a Data Warehouse.  Obviously, the question deals with business rules defined on collections of objects – not the most popular topic among decision modelers. Continue reading

Another DMN Decision Model (executable!)

Today Nick Broom published his own example of a decision model based on his understanding of the current version of the DMN standard. Nick is a business analyst and a well-known decision management practitioner, so his interpretation is very valuable as the standard is oriented to the business analysts (not to programmers). Nick’s example is supposed to make a decision whether an applicant is eligible or ineligible to a credit card. Nick described a simple credit card application process and designed decision requirements diagrams and related decision tables.

Starting to read his post, I decided that it could be helpful to make Nick’s decision model executable and to test if it actually produces the expected results. It took me several hours to do it using mainly Excel and the latest version of OpenRules BDMS.   Continue reading

My LinkedIn Discussions

LinkedIn today is probably the most popular social network for professionals. Looking for one of my old posts, I noticed that it is not so simple to find it and many people have troubles to do it. However, when you click on your name inside any discussion you will receive links to everything you posted but only within one discussion group. Here are LinkedIn discussions that I’ve started in several groups: Continue reading

OpenRules at Decision CAMP 2013

OpenRules is one of the initiators and sponsors of the DecisionCAMP-2013, the
first event for Decision Management practitioners, which will be held in San Jose, CA on Nov 4-6. This event attracted many well-known experts in the business rules and decisions management area – see the agenda. We expect ~250 attendees. OpenRules will participate in the following mini-events: Continue reading

OpenRules in Japan

EWS-2013, Tokyo

Dr. Feldman and Mr. Nakayama, CEO at Intra-Mart

I’ve just returned from my first ever trip to Japan. I am coming back home to the US with very bright impressions of the Japanese culture and people. I was especially impressed by the deep respect and high professionalism with which people in Japan perform their jobs independently of how small or important those jobs are. I deeply appreciate the friendliness and readiness to help from people on the streets of Tokyo and Kyoto that I have not seen for a while.

This visit was organized by our Japanese partner NTT Data Intra-Mart. Continue reading

Solving Rule Conflicts – Part 2

“The Sleep of Reason Produces Monsters”, Francisco Goya

 Defeasible Logic and Business Rules with Probabilities

Modern rules and decisions management systems provide effective mechanisms for development of good decision models. However, building real-world decision models people always face complex issues related to diagnostic and resolution of rule conflicts. Some systems can effectively verify decision model consistency and diagnose rule conflicts. But there are no practically used Business Rules (BR) products that claim that they may automatically resolve rule conflicts.

In the Part 1 of this series I described how end users can represent their rules in single-hit and multi-hit decision tables while avoiding rule conflicts. But is it possible to automatically resolve rule conflicts? I will discuss this problem below. Continue reading

Solving Rule Conflicts – Part 1

Representing Contradictory Rules with Single-Hit and Multi-Hit Decision Tables

Modern rules and decisions management systems provide effective mechanisms for development of good decision models. However, building real-world decision models people always face complex issues related to diagnostic and resolution of rule conflicts. Some systems can effectively verify decision model consistency and diagnose rule conflicts. But there are no practically used Business Rules products that claim that they may automatically resolve rule conflicts (at least I am not aware of them).  As a result, it becomes a responsibility of users to represent rules in such a way that allows them to avoid conflicts. Continue reading

Combining Constraint Solving with Business Rules and Machine Learning – CoCoMiLe 2013

The integration of different decision making techniques finally is finding its home under the roof of the Decision Management movement. I am glad that an integrated Constraint Programming (CP), Business Rules (BR), and Machine Learning (ML) approach is gaining in popularity as well. An interesting workshop “CoCoMiLe 2013 – Continue reading

How to compact large decision tables

A well-known problem with decision tables is that they frequently become too big and too difficult to manage.  It is also well-known that OpenRules utilizes Excel-based decision tables as its major representation mechanism for business rules.  So, I decided to share some methods used by our customers to make large decision tables more compact. Continue reading

Deploying OpenRules Applications on Cloud

A week ago at JavaOne Conference in San Francisco I had a chance to talk directly with several providers of cloud deployment solutions for Java applications. I was really impressed with a Ukrainian startup “Jelastic” that just won the Java Community’s version of Oscar and was endorsed by Dr. Gosling – read more here. Coming back home to NJ, I decided to try it myself. I took the existing web application that implements a popular game “Nim” using OpenRules decision tables and forms. It looks as follows:

Previously this web application was deployed at the local Tomcat, and I wanted to move it to the Jelastic’s cloud with minimal efforts.  And I had almost no problems of doing that! Now you may try to play Nim yourself from the cloud using this URL http://openrules.jelastic.servint.net/Nim/. What have I actually done?

Continue reading

Fischer vs. Kasparov vs. Karpov

On a long flight back to the US I had a few hours to kill. So, I decided to implement one of my favorite modeling tests that I used to give to my students and they always enjoyed it. This time I wanted to try it myself with the newest OpenRules Decision Modeling facilities (see Rule Solver).

Virtual Chess Tournament
Three world champions Fischer, Kasparov, and Karpov played in a virtual chess tournament. Each player played 7 games against two other opponents. Each player received 2 points for a victory, 1 for a draw, and 0 for a loss. We know that Kasparov, known as the most aggressive player, won the most games. Karpov, known as the best defensive player, lost the least games. And Fischer, of course, won the tournament. Continue reading

Rule Engines: RETE and Alternatives

The famous RETE algorithm was invented by Dr. Charles Forgy more than 30 years ago and it still remains the foundation for most implementations of inferential rule engines.  Recently Carole-Ann asked the question: why after all these years there were no practical alternatives to RETE? Continue reading

Modeling Decisions for Scheduling and Resource Allocation Problems

“Reality is built in wonderful simplicity”, Eliyahu Goldratt “The Choice

Scheduling and Resource Allocation are traditionally considered as very complex business problems. They are usually out of reach for the most rule engines.  I personally learned how to deal with these complex problems during my real-world consulting practice by applying a great product called “ILOG Scheduler” written by Claude LePape and Jean-Francois Puget 20 years ago. I’ve just googled the product name and got this User Manual that has over 600 pages with a lot of C++ code. I used to teach ILOG Solver/Scheduler courses and will reuse some examples borrowed from them. Continue reading

In memory of Eliyahu Goldratt

Today searching web for goal programming sources I suddenly learned that last year Eliyahu Goldratt died. He was 64. I remember how impressed I was with his books “The Goal” and “Theory of Constraints” that helped me with an implementation of a custom supply chain system at the end of 90’s. I remember reading “The Goal” aloud to my wife – it was more than another technical book.  Not being a native English speaker, he used plain English to explain complex issues in a very unconventional way. Continue reading

Different Decision Tables for a Very Simple Use Case

The responses to the RFP of OMG  DMN (Decision Model and Notation) standard are scheduled to arrive in May of 2012. Trying to keep this process as close as possible to the everyday decision management reality, I posted several use cases at the DMN Discussion Group and tried to formulate down-to-earth questions that DMN will hopefully address. Here I want to take almost trivial rules and discuss different implementation options using decision tables. Continue reading