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bdi-mental-states

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

Updated Mar 28, 2026
Search Tags:#ontology#multi-agent systems#neuro-symbolic#sparql#rdf#bdi#mental states
One-click install
npx skills add https://github.com/whatswithavi/Ecchelon_project --skill bdi-mental-states-whatswithavi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bdi-mental-states
Source: https://github.com/whatswithavi/Ecchelon_project/tree/main/.agent/skills/bdi-mental-states
Command: npx skills add https://github.com/whatswithavi/Ecchelon_project --skill bdi-mental-states-whatswithavi

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 world states with formal class hierarchies, bidirectional properties, and OWL restrictions aligned with DOLCE. - 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 RDF notification like a payment request, generate a complete cognitive chain (world state, belief, desire, intention, plan, execution) 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 ground each belief in a world state via refersTo. Add mental processes as perdurants to track how states are generated, and attach justifications plus temporal validity intervals.

What is the Triples-to-Beliefs-to-Triples (T2B2T) paradigm?▼

T2B2T is a bidirectional pipeline where incoming RDF triples are translated into belief instances via BeliefProcess nodes, BDI deliberation runs, and results are projected back into RDF using bringsAbout. It preserves provenance from source data through cognition to output.

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

Yes, mental states stored as RDF can be synchronized with JADE agent belief bases and exported or imported as Turtle. JADEX goals can query the ontology graph for target and drop conditions using SPARQL ASK queries.

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

Use competency queries that check structural constraints, such as every intention fulfilling a desire, every belief referencing a world state, and plans having begin and end tasks. Validation queries use FILTER NOT EXISTS patterns and should return empty result sets.

What are common mistakes when modeling BDI mental states?▼

Common pitfalls 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. Keep reasoning chains to three levels to control inference cost.

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