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bdi-mental-states

Transform RDF context into BDI agent mental states using formal ontology patterns.

Updated May 18, 2026
Search Tags:#ontology#multi-agent systems#neuro-symbolic#sparql#rdf#bdi#mental states
One-click install
npx skills add https://github.com/fts-pro/FTS-MMIS-AFRIKA --skill bdi-mental-states-fts-pro
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bdi-mental-states
Source: https://github.com/fts-pro/FTS-MMIS-AFRIKA/tree/main/.agent/skills/bdi-mental-states
Command: npx skills add https://github.com/fts-pro/FTS-MMIS-AFRIKA --skill bdi-mental-states-fts-pro

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires rdflib, and includes references (resource) components.

What problem does it solve? Modeling agent cognition with beliefs, desires, and intentions requires consistent ontological structure, temporal grounding, and traceable reasoning chains that ad-hoc RDF modeling fails to provide. ## Core Features & Use Cases - BDI Ontology Modeling: Structure beliefs, desires, intentions, plans, and mental processes using formal class hierarchies aligned with DOLCE and reused ontology design patterns. - T2B2T Pipeline: Implement the Triples-to-Beliefs-to-Triples paradigm to consume external RDF context and project deliberation results back as linked data. - Framework Integration: Translate BDI models into SEMAS production rules, JADE/JADEX agent structures, and Logic Augmented Generation pipelines that constrain LLM outputs. - Use Case: Given an RDF notification that a payment was requested, generate the belief, desire, and intention chain with justifications and temporal validity, then validate it with SPARQL competency queries. ## Quick Start Model the agent mental states for this RDF context using the BDI ontology, including beliefs, desires, intentions, justifications, and temporal validity intervals.

Frequently Asked Questions about bdi-mental-states

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

FAQPage Schema
How do I model BDI agent mental states in RDF?▼

Model beliefs, desires, and intentions as endurants linked by motivates and fulfils properties, and mental processes as perdurants that generate them. Ground every belief in a WorldState via refersTo and attach Justification instances for traceability.

What is the T2B2T paradigm in BDI modeling?▼

T2B2T (Triples-to-Beliefs-to-Triples) is a bidirectional pipeline where incoming RDF triples are translated into belief instances via BeliefProcess, and after deliberation the results are projected back into RDF using bringsAbout on plan executions.

Can BDI ontology models integrate with JADE or JADEX agents?▼

Yes, BDI ontology instances map to JADE agent belief, desire, and intention structures, and to JADEX goals with target and drop conditions expressed as SPARQL ASK queries. Mental states can be exported and imported as Turtle.

How do I validate a BDI ontology implementation with SPARQL?▼

Use competency queries that check motivational chains, such as which beliefs motivated a desire or which desire an intention fulfils, plus validation queries ensuring every intention fulfils a desire and every belief references a world state.

What are common mistakes when modeling BDI mental states?▼

Common mistakes include conflating mental states with world states, omitting temporal validity intervals, using monolithic beliefs instead of hasPart composition, and skipping the plan layer between intentions and actions.

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