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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Developing Developers

I can teach someone the Python language in a week. I can’t teach them how to program in Python in a week unless they are already a skilled programmer.” Brian Jones

Our old friend Brian Jones published an interesting article “Developing Developers“. Here is an extract: The idea that coding was “mechanical” led to the offshoring movement and the claim that we don’t need programmers because “coding is a monkey task and we’ve got hundreds of coders who can code what they are asked for.” It didn’t work. I always asked the question “Where will you get people to give the coders good designs?” The answer was always “Our senior people.” The obvious question “Where will you get senior people when you have cut off the pipeline of programmers?” always went unanswered. Link

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Businesses Require Better Goal Management

Jim Sinur: “Better goal management requires a new level of transparency and communication capabilities than in the past and follows a consistent goal cycle. While there still will be the issue of variations by legal system and location, the adaptation of staff and automation will have to be faster and sharper than in the past. While there will still be steady-state goals and boundaries periods, the change increases its velocity. What are the foundations for goals in a changing world? This post will dig into the primary foundations around goals.” Link

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DecisionCAMP-2022 Update

Dates: Sep 26-28 Online

The website is up and running. Free registration

Call for Presentations – send a brief abstract by July 10

Keynote: “The Evolution of Decisioning in IT, and What Happens Next” by Paul Vincent

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DMN in Python

We received this email from Russell McDonell: “As a Python developer, I was interested in using DMN within my Python applications. Specifically I wanted to use DMN in clinical decisions using FHIR and cds-hooks. So I developed pyDMNrules (gitHub repository) which is based upon a Python implementation of FEEL – pySFeel (gitHub repository). Its rule input is an Excel workbook where the rules tables have to ‘look’ like the examples in the DMN specification (double line borders).”

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What Humans Lose When We Let AI Decide

“It’s been more than 50 years since HAL, the malevolent computer in the movie 2001: A Space Odyssey, first terrified audiences by turning against the astronauts he was supposed to protect. That cinematic moment captures what many of us still fear in AI: that it may gain superhuman powers and subjugate us. But instead of worrying about futuristic sci-fi nightmares, we should instead wake up to an equally alarming scenario that is unfolding before our eyes…” Read more

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Applying DMN to Model and Execute Legislations

Date: Wed, February 23, 2022 at 12:00pm EST
Title: “Applying DMN to Model and Execute Legislations
Presenter: Vincent van Dijk from Pharosius.nlRecording
AbstractIn this session Vincent van Dijk will share his experience applying DMN for building the Digital System for Environment and Planning Act in the Netherlands described here. Please register for free. Issues to be discussed:

  • how can we minimize translations and directly execute DMN?
  • how do we combine models from different sources to deliver a single conclusion?
  • how do we implement dynamic questioning and how does this help the end users?
  • how do we deal with the declarative character of DMN in the dialogue with the end user?
  • is DMN suitable to model legislation and can models be easily read by legal experts?
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Augmented BPMS: A Research Manifesto

A group of researchers (many of whom are associated with Declarative AI and indirectly with DecisionCAMP) just published the manifesto “Augmented Business Process Management Systems“: “While traditional BPMSs encode pre-defined flows and rules, an ABPMS augmented by AI is able to reason about the current state of the process (or across several processes) to determine a course of action that improves the performance of the process.” This manifesto outlines the lifecycle of processes within an ABPMS, discusses core characteristics of an ABPMS, and derives a set of challenges to realize systems with these characteristics. Link

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Learning Jointly from Rules and Data

Today’s post in Google AI Blog “Controlling Neural Networks with Rule Representations” introduces a novel approach that does not require machine learning models retraining to adapt the rule strength. In real-world domains where incorporating rules is critical – such as physics and healthcare – they demonstrate the effectiveness of Controllable Rule Representations in teaching rules for deep learning. Link

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DMN 1.4 and Beyond

Denis Gagne, a member of DMN Task Force and the founder of Trisotech, presented the latest news in the DMN standard during the DecisionCAMP monthly session on Jan 25. Watch the recording at https://youtu.be/3a4-fbhfnTU

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