Complexity of Probabilistic Reasoning for Neurosymbolic Classification Techniques

arXiv:2404.08404v1 Announce Type: cross
Abstract: Neurosymbolic artificial intelligence is a growing field of research aiming to combine neural network learning capabilities with the reasoning abilities of symbolic systems. Informed multi-label classification is a sub-field of neurosymbolic AI which studies how to leverage prior knowledge to improve neural classification systems. A well known family of neurosymbolic techniques for informed classification use probabilistic reasoning to integrate this knowledge during learning, inference or both. Therefore, the asymptotic complexity of probabilistic reasoning is of …

abstract artificial artificial intelligence arxiv capabilities classification complexity cs.ai cs.cc cs.lg cs.sc intelligence knowledge network neural network prior reasoning research studies systems type