Category Archives: Decision Making

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

Posted in Decision Making, Decision Modeling, Event-driven, Knowledge Representation, Machine Learning | Leave a comment

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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The Decision-Making Side of Machine Learning

Michael I. Jordan is a professor at Berkeley and one of the most influential people in machine learning, statistics, and artificial intelligence. Watch his recent presentation: “Much of the recent focus in machine learning has been on the pattern-recognition side … Continue reading

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Real-Time Decision-Making

How does your Decisioning Platform support real-time decision-making? Coolfire: “In order to make real-time decision-making a core organizational capability, it’s time for organizations of all kinds to invest in a platform designed to make their data actionable. That means utilizing a … Continue reading

Posted in Decision Making, Digital Decisioning, Event-driven, Reactive Rules | Leave a comment

Decision analytics: What is AI?

Prof. Warren B Powell from Princeton University: “The most common types of AI come in three flavors: rules, machine learning, and making decisions (“optimization”). Rules are used for guiding computers to identify patterns or make recommendations, and have to be … Continue reading

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