bdi-mental-stateslisted

# BDI Mental State Modeling Transform external RDF context into agent mental states (beliefs, desires, intentions) using formal BDI ontology patterns. This skill enables agents to reason about context through cognitive architecture, supporting deliberative reasoning, explainability, and semantic interoperability. **Core insight**: BDI modeling gives agents traceable reasoning chains -- every belief links to a justification, every desire to motivating beliefs, every intention to fulfilling desires. ## When to Activate - Processing external RDF context into agent beliefs about world states - Modeling rational agency with perception, deliberation, and action cycles - Enabling explainability through traceable reasoning chains - Implementing BDI frameworks (SEMAS, JADE, JADEX) - Augmenting LLMs with formal cognitive structures (Logic Augmented Generation) - Coordinating mental states across multi-agent platforms - Tracking temporal evolution of beliefs, desires, and intentions ## Decision Tree: BDI Modeling Approach ``` What is the primary goal? +-- Explainability and traceability --> Full BDI ontology with Justification instances +-- Bidirectional RDF integration --> T2B2T paradigm (Triples-to-Beliefs-to-Triples) +-- LLM augmentation with constraints --> Logic Augmented Generation (LAG) +-- Executable agent behavior --> SEMAS rule translation from BDI to production rules +-- All of the above --> Combine approaches; each addresses different concern ``` ## Core Concepts ###