18th Japanese Society for Artificial Intelligence General-Purpose Artificial Intelligence Meeting Group (SIG-AGI) (
2021)
Copy
BIBTEX
Abstract
I will review the main problems concerning commonsense reasoning in machines and I will present resent two different applications - namaly: the Dual PECCS linguistic categorization system and the TCL reasoning framework that have been developed to address, respectively, the problem of typicality effects and the one of commonsense compositionality, in a way that is integrated or compliant with different cognitive architectures thus extending their knowledge processing capabilities
In doing so I will show how such aspects are better dealt with at different levels of representation
and will discuss how the adoption of a cognitively inspired approach be useful in the
design and implementation of the next generation AI systems mastering commonsense.