Category Archives: Decision Modeling

Decision-Centric RPA

Arash Aghlara compares traditional Robotic Process Automation (RPA) with decision-centric RPA when both robots and staff share the logic for repetitive operational business decisions. “Enabling robots to make such decisions is not about technologies like AI, Machine Learning, Neural Networks, Predictive Analytics, etc. … Continue reading

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Decisioning Challenges of Driverless Cars

It is a lot harder to make an autonomous car than to sell the idea to AI-obsessed audiences. Christian Wolmar, the British author and broadcaster, said in this interview: “This is a fantasy that has not been thought through, and … Continue reading

Posted in Artificial Intelligence, Decision Modeling, Human-Machine Interaction, Machine Learning, Trends | 1 Comment

Decision Optimization for Dynamic Pricing

FICO posted an interesting article “Fair Pricing with Price Optimisation”. A similar system “Using Machine Learning, Business Rules, and Optimization for Flash Sale Pricing” has been developed by OpenRules.  These examples demonstrate the power and flexibility of Decision Optimization when business rules, … Continue reading

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Solutions to Nov-2018 Challenge “Vacation Days Advanced”

We’ve already received 3 submissions with solutions to our November challenge “Vacation Days Advanced” using different tools: FICO Blaze Advisor, OpenRules, and DT5GL . Contrary to the 2016 challenge “Vacation Days”, this one doesn’t have inter-rules relationships like “apply this rule only … Continue reading

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Amazon automates buying and stocking decisions

Machines are beating people at the critical inventory decisions that separate the winners and losers in retail. For the staffers deciding how many books, games or plastic pool toys to peddle, the tradeoff can be stark: Order too little and … Continue reading

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Challenge Sep-2018 “Balanced Assignment”

This challenge deals with assignment of people to certain activities, for instance: assigning students to project groups or assigning professors to offices.  We are using the problem formulation and test data provided by Prof. Robert Fourer (AMPL). We expect that not … Continue reading

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How DMN could help to explain ML outcome

Dr Jan Purchase just published an article “Better AI Transparency Using Decision Modeling“, in which he describes several possible ways to provide reasonable explanations to the outcome of machine learning algorithms. Jan without hesitations describes practical limitations of the described approaches.  Jan … Continue reading

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