Mapping CBT Cognitive Models into Executable Prolog Rules: A CDC Demonstration

General
1

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

Framework Overview

  • CDC represents knowledge as structured triples: <Concept, Relation@Domain, Concept'>.

  • 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

% 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]

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.