# Mapping CBT Cognitive Models into Executable Prolog Rules: A CDC Demonstration
**URL:** https://swi-prolog.discourse.group/t/mapping-cbt-cognitive-models-into-executable-prolog-rules-a-cdc-demonstration/9379
**Category:** General
**Created:** [November 13, 2025, 12:25pm UTC](https://swi-prolog.discourse.group/t/mapping-cbt-cognitive-models-into-executable-prolog-rules-a-cdc-demonstration/9379 "2025-11-13T12:25:46Z")
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### Author:  [@PartnerDAO](https://swi-prolog.discourse.group/u/PartnerDAO)
#### Post date: [November 13, 2025, 12:25pm UTC](https://swi-prolog.discourse.group/t/mapping-cbt-cognitive-models-into-executable-prolog-rules-a-cdc-demonstration/9379/1 "2025-11-13T12:25:46Z")
Hi everyone,
I’ve been experimenting with encoding multi-round CBT (Cognitive Behavioral Therapy) dialogues using **Domain‑Contextualized Concept Graphs (CDC)** in Prolog. The CDC framework is described in the paper:
> Li C., Wang Y. (2025). _Domain‑Contextualized Concept Graphs: A Computable Framework for Knowledge Representation_. arXiv:2510.16802. [PDF](https://arxiv.org/abs/2510.16802?utm_source=chatgpt.com)
#### **Framework Overview**
- CDC represents knowledge as structured triples: ``.
- It allows bridging **natural language → cognitive/clinical concepts → reasoning rules** , making knowledge both **computable and logically verifiable**.
- This is particularly useful for multi-layered cognitive modeling, such as CBT dialogue analysis, where concepts, symptoms, and interventions can be formalized.
#### **Why this matters for Prolog**
1. **Executable theory validation** – Any model formalized in CDC can be represented as Prolog facts and rules, enabling rigorous logic verification.
2. **Multi-layer reasoning** – CDC captures mappings from natural language statements to cognitive patterns and further to therapeutic reasoning, spanning psychological, behavioral, and neurobiological domains.
3. **Traceable and interpretable AI** – Each inference is fully transparent, allowing the reasoning chain to be inspected and verified.
4. **Extends Prolog’s traditional scope** – Beyond educational exercises or toy problems, this demonstrates that Prolog can serve as a **cross-disciplinary symbolic AI platform** , executing and validating complex cognitive models.
#### **Minimal Example**
```prolog
% Example CDC fact: input natural language concept
cdc_raw(1, "can't do anything right", 'CBT cognition', 'manifests_as', 'all-or-nothing thinking').
% Mapping to a cognitive pattern
map_cdc_to_pattern(_, 'CBT cognition', 'manifests_as', 'all-or-nothing thinking', 'all-or-nothing thinking', 0.8).
```
> This shows how a single CBT cognitive statement can be mapped into an executable Prolog rule, enabling pattern recognition and further reasoning.
#### **Demo / Repository**
The full prototype and example dialogue encoding can be found here:
[[GitHub link]](https://github.com/PartnerDAO/ominimedical/tree/main/examples/Prolog)
I would be glad to receive feedback from the community regarding **logic representation, rule design, or potential improvements** for cross-domain cognitive modeling in Prolog.