A new theoretical framework for modeling concepts that allows them to combine reflecting the way humans do, with a good related-work on other concept frameworks in AI

Martha Lewis, Jonathan Lawry, Hierarchical conceptual spaces for concept combination, Artificial Intelligence, Volume 237, August 2016, Pages 204-227, ISSN 0004-3702, DOI: 10.1016/j.artint.2016.04.008.

We introduce a hierarchical framework for conjunctive concept combination based on conceptual spaces and random set theory. The model has the flexibility to account for composition of concepts at various levels of complexity. We show that the conjunctive model includes linear combination as a special case, and that the more general model can account for non-compositional behaviours such as overextension, non-commutativity, preservation of necessity and impossibility of attributes and to some extent, attribute loss or emergence. We investigate two further aspects of human concept use, the conjunction fallacy and the “guppy effect”.

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