Compressing Decision Tables

The DMC Challenge Sep-2020 deals with compression of decision tables trying to replace relatively large decision tables with “almost” equivalent but smaller decision tables. It is only natural to apply Machine Learning to this problem as it allows us to automatically discover business rules from the sets of labeled historical data records. So, I decided to use the open source Rule Learner to address this problem. In this post I will describe how I approached this problem with these implementation steps:

  1. Write a simple generator of data instances with various combinations of known attributes
  2. Run the existing decision table using OpenRules to produce labeled instances
  3. Feed the labeled instances to Rule Learner (or SaaS Rule Learner) to automatically discover a new decision table and evaluate its performance.

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Integrated Use of Rule Engines and Constraint/Linear Solvers

Operational business problems can be defined by a set of decision variables and a set of rules that specify relationships between these variables – see the formal definition. This definition considers a decision as a solution of such a problem, but it doesn’t assume anything about ‘HOW’ how decisions will be produced. It means decisions can be found by applying any rule engine, a DMN engine, a constraint or MIP solver, a custom piece of software written in any programming language, a manually provided expert’s decision, or their various combinations. Continue reading

Building Decision Models for Challenge “Balanced Assignment”

DMCommunity Sep-2018 Challenge “Balanced Assignment” gives an example of a complex business problem with a serious optimization component. This problem deals with the assignment of people to different project groups. Usually, such problems require deep knowledge of optimization techniques. My interest was to build a decision model for this problem and to investigate what can be done by business people and where the involvement of optimization experts is necessary. So, I attempted to use a business-friendly approach to represent and to solve this complex problem. It was not a simple journey, and this article describes what I did successfully and where I failed. Link

“Model-based” vs. “Method-based” Approaches to Decision Modeling

In Aug-2018 Prof. Robert Fourer gave a tutorial “Model-based Optimization“, in which he compares two essentially different approaches to modeling optimization problem: “model-based” vs. “method-based”. He is using a relatively complex “Balanced Assignment” problem to demonstrate his points. While Fourer’s tutorial deals with optimization, I believe the same arguments are directly related to Decision Modeling that so far mainly remains method-based. During DecisionCAMP-2018 we had interesting (and sometimes hot) discussions about these two approaches and in my closing remarks I described the major differences between them as follows: Continue reading

Decision Management and Semantic Reasoning

Considering the upcoming conferences, I was asked by Harold Boley to write about a possible integration of Semantic Reasoning and Business Decision Management. Today I posted an article at the RuleML Blog and decided to reproduce it here as well but in a bit more friendly format.
On September-2018 DecisionCAMP and RuleML+RR will be co-located again for the third time during the LuxLogAI-2018 summit in Luxembourg. These two events represent different but closely related fields of the knowledge representation movement: Business Rules & Decisions Management and Semantic Reasoning. In this post I want to talk about relationships between these two fields and events.

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Happy 15th Birthday, OpenRules!

Today is exactly 15 years since OpenRules, Inc. was incorporated on Feb. 24, 2003. It’s a quite serious milestone, so I decided to write a few words for this occasion. A year ago, I described a brief history of our company and key factors that made it successful. 2018 was an extremely successful year for OpenRules as well: we improved the product and many major corporations became our new customers. But in this post I want to look to the future and to share some of our upcoming and long term plans. Continue reading