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bdi-mental-states

Transform RDF context into BDI mental states with Turtle triples and SPARQL validation.

Updated Apr 15, 2025
Search Tags:#ontology#sparql#rdf#agent-architecture#bdi#mental-states
One-click install
npx skills add https://github.com/khrore/nix-config --skill bdi-mental-states-khrore
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bdi-mental-states
Source: https://github.com/khrore/nix-config/tree/main/dotfiles/common/.config/opencode/skills/bdi-mental-states
Command: npx skills add https://github.com/khrore/nix-config --skill bdi-mental-states-khrore

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Map external RDF knowledge into explicit, traceable Belief-Desire-Intention mental states so agents can reason, plan, and explain decisions in multi-agent and LLM-augmented systems. The Skill reduces ambiguity between world state data and agent cognition by providing structured ontology patterns, temporal validity, and justification links for every mental entity.

Core Features & Use Cases

  • Triples-to-Beliefs-to-Triples (T2B2T): Translate incoming RDF into Belief instances, drive desire and intention formation, then project intentions and plan executions back to RDF.
  • Ontology-First Modeling & Validation: Provides BDI ontology patterns, OWL restrictions, SPARQL competency queries, and consistency checks to validate generated mental states.
  • Integration Patterns: Includes Logic-Augmented Generation guidance, SEMAS/JADE/JADEX mappings, RDF triple-store examples, and multi-agent FIPA messaging for coordination and execution.
  • Temporal and Explainable Reasoning: Ensures mental entities carry hasValidity intervals and isJustifiedBy links for provenance and explainability.

Quick Start

Convert the given RDF context into Turtle triples representing beliefs, desires, and intentions with temporal validity and justifications, and validate the output against the BDI ontology.

Frequently Asked Questions about bdi-mental-states

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert RDF triples into BDI mental states for agent reasoning?▼

You convert RDF context into BDI mental states by generating Turtle triples for beliefs, desires, and intentions. This process includes adding temporal validity intervals and justification links to ensure explainable agent deliberation.

What is the T2B2T approach for mapping RDF to agent mental states?▼

The T2B2T approach translates incoming RDF context into Belief instances to drive desire and intention formation, then projects intentions and plan executions back into RDF triples for bidirectional ontology-driven agent reasoning.

Can I validate generated BDI ontology constraints using SPARQL competency queries?▼

Yes, you validate generated BDI mental states by applying SPARQL competency queries and consistency checks against provided BDI ontology patterns and OWL restrictions to ensure valid mental state representations.

Does this BDI mental state mapping work with JADE and JADEX multi-agent frameworks?▼

Yes, the mapping includes integration patterns and mappings for SEMAS, JADE, and JADEX frameworks, alongside RDF triple-store examples and multi-agent FIPA messaging for coordinated execution workflows.

How do I add temporal validity and provenance justifications to RDF-based agent beliefs?▼

You add temporal validity and provenance by assigning hasValidity intervals and isJustifiedBy links to every mental entity, ensuring RDF-based agent beliefs carry structured provenance for explainable reasoning.

When do I need ontology-driven BDI mental states for LLM augmentation pipelines?▼

You need ontology-driven BDI mental states for LLM augmentation pipelines when multi-agent systems require structured reasoning, planning, and explainable decisions with bidirectional RDF mapping to reduce ambiguity between world state data and agent cognition.

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