TTR at the SPA: Relating type-theoretical semantics to neural semantic pointers - Larsson, Staffan; Cooper, Robin; Ginzburg, Jonathan; Lücking, Andy (Proceedings of Natural Logic Meets Machine Learning IV, 2023)
This paper considers how the kind of formal semantic objects used in TTR (a theory of types with records, Cooper, 2023) might be related to the vector representations used in Eliasmith (2013). An advantage of doing this is that it would immediately give us a neural representa- tion for TTR objects as Eliasmith relates vec- tors to neural activity in his semantic pointer architecture (SPA). This would be an alternat- ive using convolution to the suggestions made by Cooper (2019a) based on the phasing of neural activity. The project seems potentially hopeful since all complex TTR objects are con- structed from labelled sets (essentially sets of ordered pairs consisting of labels and values) which might be seen as corresponding to the representation of structured objects which Elia- smith achieves using superposition and circular convolution.