Workflow 2

Workflow Instructions

In Workflow 1, we exported a Structural Prior Dictionary, including the Causal Structural Priors, and then imported this dictionary as an Arc Dictionary to create a causal network with these priors.
In this Workflow 2, we will immediately utilize the Causal Structural Priors to machine-learning a new network without the export/import step.
So, our starting point is the machine-learned network, for which Hellixia has already obtained the Causal Structural Priors. The Structural Prior icon indicates that Structural Priors are associated with the network.
However, these new Causal Structural Priors have not been used for updating the arc directions in the network.

Select Menu > Learning > Unsupervised Structural Learning > Taboo.

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Like Arc Constraints, Structural Priors, Temporal Indices, and Filtered States, Causal Structural Priors impose constraints on learning. As a result, EQ-based algorithms are not available under those conditions.

This newly learned network now reflects the causal order obtained from ChatGPT.
With the final arc directions in place, we should arrange the nodes into a more intuitive layout, i.e., positioning parent nodes above child nodes.
Select Menu > View > Layout > Genetic Grid Layout > Top-Down Repartition.
Note that the algorithm keeps searching for a better layout until you stop the process by clicking the red buttonto the left of the Progress Bar.