Perspectives of Neural-Symbolic Integration

By Barbara Hammer, Pascal Hitzler. 2007

97 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Luciano Serafini
2. A.S. d'Avila Garcez
3. L. C. Lamb
4. Marco Gori
5. Ben Goertzel

Citations in the corpus

• Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning (2019, background): “The integration of learning and reasoning through neural-symbolic computing has been an active branch of AI research for several years [14, 16, 17, 21, 25, 42, 53].”
• DeepProbLog: Neural Probabilistic Logic Programming (2018, methodology): “Most of the work on combining neural networks and logical reasoning comes from the neuro-symbolic reasoning literature [7, 31].”
• Artificial General Intelligence: Concept, State of the Art, and Future Prospects (2009, background): “There are research results doing inference and language processing using subsymbolic architectures, some of which are reviewed in (Hammer and Hitzler, 2007); but these mainly involve relatively simplistic problem cases.”
• Neurosymbolic AI: the 3rd wave (2020, unknown): “Neural-symbolic computing has been an active area of research seeking to establish such a bridge for several years [4, 26, 16, 20, 35, 43, 80, 93].”