Cognition · Software component
Logic Conclusion Verbalizer
Software componentCognitionCognition & Memoryarc:LogicConclusionVerbalizer
A component that converts formally derived conclusions back into natural language, citing the logic rule applied to make the inference transparent.
Responsibility. Renders formal conclusions as rule-citing natural-language explanations.
Also known as: Logic Agent stage 3, Explanation generator, Rule explanation generator, Neural language generator for inference results
Relationships
is invoked by dependency
reads dependency
receives data from dynamic
sends data to dynamic
is orchestrated by control
Design guidance
- SHOULD connect each decision to domain rationale rather than rule numbers for non-technical users.
- SHOULD generate explanation depth appropriate to each audience (full trace for experts, plain summaries for patients, statistics for auditors).
Classification
- Patterns
- Audience-tailored explanation depthTrace-to-rationale verbalisation
- Frameworks & regulations
- Fair Credit Reporting Act (specific reasons for credit denial)EU GDPR (right to explanation for automated decisions)
Sources
- Ch3.9: T. Nguyen, "Reasoning Quality," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 3.9. ISBN: 9798244538229.
- Ch5.11: T. Nguyen, "Rule-Based Decision Making Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 5.11. ISBN: 9798244538229.
- Ch5.13: T. Nguyen, "Hybrid Decision Systems Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 5.13. ISBN: 9798244538229.