What is randomness?

Randomness is pretty important. Science would fall apart without it. Not just because randomised control trials wouldn’t be randomised, but because almost any experiment would produce junk. Say Galileo dropped his spheres of different weights, but their falls were affected by other (external) things non-randomly. The results would be biased or inconsistent, and we might …

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A Bite-Sized Introduction to Bayesian Networks

A Bayesian network is traditionally defined as a directed acyclic graph (DAG), made up of nodes and arrows, coupled with discrete conditional probability tables (CPTs). If an arrow starts at one node and points to another, the first node is called the parent, and the second the child — but only for that arrow. Each …

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Make-Believe R24: Connections

A little bit of an unintentional pause in the release rhythm, but we’re hopefully back to an ordinary schedule now. This release has a few API updates, plus one addition to the GUI: the ability to highlight d-connected nodes. In case you’re not familiar with d-connectedness: Two nodes are d-connected (given existing evidence) if it …

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Make-Believe R23: Types are a Changing

The main additions in this release revolve around being able to change the type of a node (still in progress), and improvements to editing node definitions. There is also a tiny bit of (non-functioning) foreshadowing for some bigger changes to node definitions. Make-Believe R23 [or view latest] Changes: Add editing for function tables (deterministic/discrete and …

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Make-Believe (R22): Command and Control

This version mostly focuses on giving access to Make-Believe outside of the browser. There are two components to this: an API and a standalone desktop app. I describe those in a bit more detail below. The only other significant change in this version is support for text boxes from .xdsl files (see image at right). …

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