Tag: AI knowledge representation
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Optimizing Horn DL Ontologies for ABox and Query Fitting
Explore efficient methods for fitting Horn DL ontologies to ABox and queries, addressing complexity and decision procedures in AI knowledge representation.
Optimizing Assumption-Based Argumentation Frameworks
Discover new splitting methods to reduce computational complexity in Assumption-Based Argumentation Frameworks for efficient reasoning.
NeSyCat: Monad-Based Semantics for Neurosymbolic AI
Discover NeSyCat, a monad-based framework unifying semantics in the ULLER neurosymbolic AI system for enhanced modularity and reasoning.
DALM: Structured Domain-Algebraic Language Model Explained
Discover DALM, a domain-algebraic language model using three-phase structured generation to improve multi-domain knowledge accuracy and coherence.
Neuro-Symbolic AI Robots: Learning with Closed Knowledge
Explore neuro-symbolic AI robots using closed knowledge assumptions for enhanced learning, reasoning, and handling inconsistencies in strong AI systems.