Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces

Understand

Analogical Reasoning problems challenge both connectionist and symbolic AI systems as these entail a combination of background knowledge, reasoning and pattern recognition.

• While symbolic systems ingest explicit domain knowledge and perform deductive reasoning, they are sensitive to noise and require inputs be mapped to preset symbolic features.
• Connectionist systems on the other hand can directly ingest rich input spaces such as images, text or speech and recognize pattern even with noisy inputs.
• However, connectionist models struggle to include explicit domain knowledge for deductive reasoning.