felipecustodio Overview & Purpose
Analogical Reasoning maps structural relationships from a well-understood source domain to solve novel problems in a target domain. It enables creative cross-domain problem solving and intuitive explanations.
When to Use
- Novel Problem Solving: Applying proven architecture patterns (e.g., assembly line) to new fields (e.g., software CI/CD pipelines).
- Simplifying Complex Concepts: Explaining abstract technical systems using intuitive real-world analogs.
Execution Workflow
- Identify Target Domain: Define the problem or concept that needs solving/explanation.
- Select Source Domain: Identify a familiar domain sharing deep structural similarities (not surface similarities).
- Map Structural Relationships: Align elements of Source $\to$ Target ($A \to X, B \to Y$).
- Transfer Insights: Apply known solutions from the source to generate hypotheses for the target.
- Validate Limits: Identify where the analogy breaks down to avoid false equivalences.
Expected Output Contract
### Analogical Transfer
- **Source Domain**: [Familiar System]
- **Target Domain**: [Novel Problem]
- **Structural Mapping**:
- `Source Concept A` -> `Target Concept X`
- **Inferred Solution**: [Transferred Insight]
- **Analogy Breakdown / Limitations**: [Where analogy fails]
Scripts
scripts/analogical_reasoning.py- Deterministic evaluation, state validation, and CLI tool for analogical-reasoning.