neurosymbolic approaches

Dave, thanks
No I did not have that reference, did not come up in searches, shall check
it out
any chance you may want to enter it in the zotero library
thank you!!
PDM

On Sat, Feb 15, 2020 at 6:59 PM Dave Raggett <dsr@w3.org> wrote:

> Hi Paola,
>
> On 15 Feb 2020, at 01:17, Paola Di Maio <paola.dimaio@gmail.com> wrote:
>
> I am working on a Neurosymbolic approaches for AI KR.
>
>
> I hope that your paper will cite Chris Eliasmith’s computational
> neuroscience team at the University of Waterloo. They have worked
> extensively on biologically accurate models describing how symbolic
> information can be expressed and manipulated by neural networks.
>
> https://uwaterloo.ca/systems-design-engineering/profile/celiasmi
>
> *"Higher-level cognitive functions in biological systems are made possible
> by Semantic Pointers. Semantic Pointers are neural representations that
> carry partial semantic content and are composable into the representational
> structures necessary to support complex cognition."*
>
> Semantic pointers are vectors in n-dimensional spaces corresponding to
> concurrent patterns of firing across bundles of nerve fibres. It is
> essentially the same idea as a chunk, i.e. a collection of properties,
> whose values identify other chunks. Using addition
> and circular convolution, multiple semantic pointers can be stored
> and retrieved within a single vector.  Mathematical details are available
> at:
>
> https://www.nengo.ai/nengo-spa/user-guide/spa-intro.html
>
> There is also a downloadable python package for testing and deploying
> neural networks, see: https://www.nengo.ai/
>
> Best regards,
>
> Dave Raggett <dsr@w3.org> http://www.w3.org/People/Raggett
> W3C Data Activity Lead & W3C champion for the Web of things
>
>
>
>