Category Archives: Decision Making

Christopher Columbus, global warming and mathematical optimization

In this highly popular article IBM’s Alex Fleischer wrote: “One of the levers is the mathematical optimization of business decision making, made possible by data and the deployment of decision models associated with constraint programming. Or, put more simply: an algorithm … Continue reading

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Decision-Making vs. Problem Solving

This post Decision-Making: How to Determine the Best Possible Choices defines decision-making as “the process by which people come to actionable decisions after a careful consideration of the facts and values of the situation and parties involved. Decision-making could either be rational or … Continue reading

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Decision Intelligence 101

“Decision Intelligence is a practical approach designed to improve decision-making by first understanding and then engineering the way decisions are made and how outcomes are evaluated, managed, and improved based on feedback.” Decision intelligence has three key business benefits: Link

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From “Decision Support” to “Reengineering Decision Making”

In Nov-2020, Gartner published a report ‘The Future of Data and Analytics: Reengineering the Decision, 2025’. It stated, “Decision making is becoming more connected, more contextual and more continuous. The current state of decision making is unsustainable. We define reengineering … Continue reading

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AI in Decision Domain 

An interesting discussion has started by this LinkedIn post: Typically, we analyze data and models from the operational domain. However, no amount of crunching on this data will reveal opportunities for decision advantage – because there is no information about … Continue reading

Posted in Artificial Intelligence, Decision Making, Decision Modeling, Human-Machine Interaction, Insurance Industry, Knowledge Representation | Leave a comment

When to Automate Decisions

A new article about decision automation in AI Building Blocks: “So far there is no unified decision method that can fit the puzzle of decision-making in organizations. For strategic and tactical decisions, practitioners continue relying on optimization and statistics but … Continue reading

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Using Episodic Memories to Predict Upcoming Events

This paper addresses an important problem in control of episodic memory to be used to predict upcoming states in an environment where past situations sometimes reoccur. One of the key benefits is reducing the risk of retrieving irrelevant memories. Read more

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Everything old is new again

Prof. Gene Freuder writes about Human-Centered AI: “human-centered”, “human-aware“, “human-AI collaboration” are, rightly, very prominent nowadays. But “everything old is new again”: I ran across an interesting twenty-year-old paper from the European Journal of Operational Research on Human centered processes and decision support … Continue reading

Posted in Business Rules, Constraint Programming, Decision Making, Human-Machine Interaction, Machine Learning | Leave a comment

Buridan’s Indecisioning

Buridan’s Principle: A discrete decision based upon an input having a continuous range of values cannot be made within a bounded length of time.  Leslie Lamport Everyday example: “You’re walking down the street and realize, to your chagrin, that you’re … Continue reading

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Pragmatic Approach to Predictive Decision Automation

In this webinar Red Hat specialists explain how explainable Predictive Decisioning can help us trust AI. Their  approach combines AI/ML, decision optimization, and traditional business rules to better understand the factors that contribute to an automated decision. They use the … Continue reading

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