bdi-mental-states

Model agent mental states by translating cognition prompts into RDF-based BDI graphs. Beliefs link to world states, Desires generate from Beliefs, and Intentions commit to Plans, enabling traceable multi-agent deliberation with enforced ontology constraints and temporal bounds.

The BDI model structures cognitive agents via Belief, Desire, and Intention states. You need it for single or multi-agent systems requiring deliberation, explainability, temporal reasoning, and ontology alignment, producing validated RDF graphs for downstream execution.

Yes, you can integrate RDF-based knowledge graphs to enable traceable reasoning. The process generates Justifications, enforces temporal validity, and applies T2B2T integration across agents, producing validated outputs suitable for runtime reasoning.

Yes, this BDI mental states approach supports integration with JADE, SEMAS, and LAG frameworks. It transforms external RDF context into formal BDI ontologies, ensuring cross-agent interoperability and runtime reasoning capabilities for cognitive agents.

Convert world state perceptions into Belief graphs by providing RDF prompts to the system. It transforms external RDF context into formal BDI mental states linked to world states, enforcing ontology constraints and producing validated RDF graphs.

BDI ontologies enforce strict ontology constraints, temporal bounds, and justification traces, which may limit flexibility in highly dynamic environments. However, these constraints ensure validated RDF graphs suitable for explainable downstream reasoning and execution.