Probabilistic Extension of Neuro-Symbolic AGI Robots based on Belnap's Typed Intensional FOL

arXiv cs.AI · 18 hours ago

Researchers extended neuro-symbolic AI based on Belnap's intensional first-order logic by incorporating probabilistic reasoning for unknown sentences using Nilsson's probability structure. The approach introduces global and local symmetry transformations to preserve knowledge while computing probability density functions through neural networks using maximum entropy principles. This enables AGI systems to combine neural learning with symbolic reasoning while handling uncertainty in logical reasoning tasks.