Automatic Propositional Causal Bayesian Network Generator
Overview
The Automatic Propositional Causal Bayesian Network Generator turns a written description of a problem into a draft Bayesian network: nodes joined by causal arcs and quantified with probability tables. Give it a question or a short description of your domain, plus any background context or modeling constraints, and it proposes the nodes, the causal arcs with explanatory comments, causal effects, and conditional probability tables.
Use it for rapid causal model prototyping and risk-centric causal modeling, or when starting from a domain question.
Inputs
- Prompt or question
- Optional General Context
- Optional modeling constraints
Outputs
- Nodes
- Causal arcs
- Arc comments
- Causal effects
- Conditional probability tables
Workflow
Prepare the network, source material, selected nodes, selected arcs, or Knowledge Files required by the function.
Confirm that Hellixia provider settings and model access are configured.
Open
Hellixia > Automatic Propositional Causal Bayesian Network Generator.Review the available options and add General Context when the model needs domain-specific guidance.
Run the function and inspect the generated graph, comments, priors, embeddings, translations, or images.
Related Functions
- Automatic Semantic Network Generator
- Propositional Causal Bayesian Network Generator
- Causal Structural Priors