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bdi-mental-states

Translate RDF context into BDI mental states with temporal validity.

Updated Jan 9, 2026
Search Tags:#ontology#multi-agent#explainability#rdf#cognitive-architecture#bdi
One-click install
npx skills add https://github.com/samvanme/SBSitev0 --skill bdi-mental-states-samvanme
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bdi-mental-states
Source: https://github.com/samvanme/SBSitev0/tree/main/claudeskills/Agent-Skills-for-Context-Engineering-main/skills/bdi-mental-states
Command: npx skills add https://github.com/samvanme/SBSitev0 --skill bdi-mental-states-samvanme

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Translate external RDF context into agent mental states (beliefs, desires, intentions) using a formal BDI ontology. This skill enables developers to map perceptual inputs to internal cognitive representations and supports explainable deliberation in multi-agent systems.

Core Features & Use Cases

  • BDI mapping: Convert world states, perceptions, and events into Beliefs, Desires, and Intentions with temporal validity and justifications.
  • World-state grounding: Link mental states to concrete WorldState instances for context-aware reasoning.
  • Explainable deliberation: Trace reasoning from perceptions through desires to intentions for auditability in complex agent interactions.
  • Multi-agent coordination: Coordinate mental states across agents, enabling collaborative planning and negotiation.
  • Planning integration: Connect desires and intentions to Plans and Tasks to drive action sequences in agent systems.
  • Interoperability with RDF ontologies: Use standard RDF/OWL patterns to enable semantic interoperability in heterogeneous environments.

Quick Start

  1. Load RDF context describing an agent perception and world state.
  2. Generate Beliefs, Desires, and Intentions using the BDI ontology.
  3. Validate consistency (e.g., each Intention fulfills a Desire, Beliefs refer to a WorldState) and inspect justification chains.

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 agent mental states using a BDI ontology from RDF data?▼

To model agent mental states, you translate external RDF context into Beliefs, Desires, and Intentions. This enforces BDI constraints to support cognitive reasoning, explainability, and interoperability across multi-agent systems.

What is the best way to map multi-agent perceptions to cognitive beliefs and Desires?▼

Mapping multi-agent perceptions involves linking concrete WorldState instances to Beliefs, which then motivate Desires. This provides context-aware reasoning and traces reasoning chains for auditability in complex agent interactions.

How does BDI reasoning enforce constraints for explainable deliberation in agents?▼

BDI reasoning enforces constraints by requiring Beliefs to reference WorldStates, Desires to be motivated by Beliefs, and Intentions to fulfill Desires. This structured mapping ensures explainable deliberation with temporal validity and justifications.

Can I use RDF and OWL patterns to coordinate mental states across multiple agents?▼

Yes, you can use standard RDF and OWL patterns to coordinate mental states across multiple agents. This enables semantic interoperability in heterogeneous environments and supports collaborative planning and negotiation.

How do I connect agent Intentions to Plans and Tasks for action sequences?▼

You connect action sequences by linking Desires and Intentions to Plans and Tasks within the BDI ontology. This planning integration drives structured action sequences and enables coordinated execution in multi-agent systems.

What are the limitations of using a BDI ontology for multi-agent coordination?▼

A limitation of using a BDI ontology is the strict requirement to validate consistency, ensuring every Intention fulfills a Desire and Beliefs refer to a valid WorldState. This enforces rigid structural constraints that require precise RDF context mapping.

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