Researchers have developed a formal Belief-Desire-Intention (BDI) ontology to better represent rational agency in artificial intelligence and cognitive sciences. This ontology aims to bridge the gap between cognitive architectures and structured knowledge representations. Experiments show its utility when integrated with Large Language Models (LLMs) for enhanced inferential coherence and with reasoning platforms for bidirectional data flow between RDF triples and agent mental states. AI
IMPACT This ontology could enable more cognitively grounded and explainable AI systems, particularly in multi-agent and neuro-symbolic applications.
RANK_REASON The cluster contains a research paper detailing a new ontology for AI agency. [lever_c_demoted from research: ic=1 ai=1.0]
- Andrea Giovanni Nuzzolese
- arXiv
- Belief-Desire-Intention (BDI)
- Large Language Models (LLMs)
- Logic Augmented Generation (LAG)
- Resource Description Framework
- Semas
- Sparna
- Triples-to-Beliefs-to-Triples (T2B2T)
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