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 within multi-agent systems.

When to Activate

Activate this skill when:

• 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
• Linking motivational states to action plans

Do not activate this skill for adjacent work owned by other skills:

• General context-window explanations or attention mechanics: context-fundamentals.
• Persistent user, entity, or conversation memory without formal BDI state: memory-systems.
• Supervisor, swarm, or handoff topology decisions: multi-agent-patterns.
• General agent evaluation rubrics or quality gates: evaluation.

Core Concepts

Mental Reality Architecture

Separate mental states into two ontological categories because BDI reasoning requires distinguishing what persists from what happens:

Mental States (Endurants) -- model these as persistent cognitive attributes that hold over time intervals:

• Belief: Represent what the agent holds true about the world. Ground every belief in a world state reference.
• Desire: Represent what the agent wishes to bring about. Link each desire back to the beliefs that motivate it.
• Intention: Represent what the agent commits to achieving. An intention must fulfil a desire and specify a plan.