Neuro-Symbolic Artificial Intelligence
An unofficial community hub for neurosymbolic AI, maintained by Augustus Haoyang Li.
Not affiliated with the NeSy AI Association. Visit the official NeSy AI conference site at nesy-ai.org
Neurosymbolic AI explores the intersection of neural networks and symbolic reasoning, aiming to build systems that combine deep learning with the interpretability and logical rigor of symbolic methods. The field draws on machine learning, knowledge representation, cognitive science, and formal logic to create AI that can both learn from data and reason over structured knowledge.
Bridging connectionist and symbolic paradigms for robust reasoning.
Structured knowledge graphs combined with learned embeddings.
Differentiable logic programming and theorem proving.
A curated collection of key readings, tools, and benchmarks in the neurosymbolic AI field.
Neural predicates integrated into probabilistic logic programs.
Real logic grounding with tensor network representations.
A language based on Datalog for integrating deep learning with logical reasoning.
Conferences, workshops, and journals where neurosymbolic AI research is presented and discussed.
Sessions and workshops at NeurIPS, AAAI, IJCAI, ICLR, and KR.
Open-source projects and tools from the neurosymbolic AI community.
Combining neural networks with answer set programs.