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bdi-mental-states

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

1|Updated May 16, 2026
Search Tags:#ontology#multi-agent systems#neuro-symbolic#sparql#rdf#bdi#mental states
One-click install
npx skills add https://github.com/ludotype/game-adventurertown --skill bdi-mental-states-ludotype
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bdi-mental-states
Source: https://github.com/ludotype/game-adventurertown/tree/main/.agent/skills/bdi-mental-states
Command: npx skills add https://github.com/ludotype/game-adventurertown --skill bdi-mental-states-ludotype

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, which ad-hoc RDF modeling fails to provide. ## Core Features & Use Cases - BDI Ontology Modeling: Structure beliefs, desires, intentions, plans, and mental processes as RDF triples 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 agents, FIPA ACL messages, and Logic Augmented Generation pipelines for LLMs. - Use Case: Given an incoming RDF notification such as a payment request, generate the full cognitive chain from world state through belief, desire, and intention to an executable plan, then validate it with SPARQL competency queries. ## Quick Start Model the agent's beliefs, desires, and intentions from the attached RDF context using the BDI ontology patterns and validate the result with the competency queries.

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 RDF instances of the BDI ontology classes, grounding each belief in a world state via refersTo and linking desires and intentions through motivates and fulfils properties. Serialize the result in Turtle and validate with SPARQL queries.

What is the Triples-to-Beliefs-to-Triples paradigm?▼

T2B2T is a bidirectional pipeline where incoming RDF triples are translated into belief instances through belief processes, BDI deliberation selects intentions and executes plans, and results are projected back into RDF using bringsAbout so downstream systems consume agent outputs as linked data.

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

Yes, BDI ontology instances map to JADE agent structures by storing mental states in an RDF graph alongside Java belief, desire, and intention objects, and to JADEX goals through SPARQL-based target and drop conditions evaluated against the ontology.

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

Run competency queries that check motivational chains, such as which beliefs motivated a desire or which desire an intention fulfills, plus validation queries ensuring every intention fulfills 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 compositional hasPart structures, skipping justifications, and building reasoning chains deeper than three levels.

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