Re: Update on work on chunk based cognitive agents

Academic/personal interest with support from the Boost 4.0 European project on smart manufacturing.

> On 19 Sep 2019, at 04:11, Paola Di Maio <paola.dimaio@gmail.com> wrote:
> 
> Thank you Dave
> hope your talk at TPAC is going well -  do you have any recordings of your talk?
> Our meeting starts soon and d virtual room should enable everyone to attend
> 
> Regarding your questions, I am interested in the KR representation aspects
> of the work. is this work academic. or for a company?
> 
> PDM
> 
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> On Thu, Sep 19, 2019 at 11:03 AM Dave Raggett <dsr@w3.org <mailto:dsr@w3.org>> wrote:
> I’ve been working on adapting ideas from John R. Anderson’s work on ACT-R, as a basis for web-based cognitive agents. This provides a framework for data and rules based upon chunks - a term from psychology for a collection of things that are easier to remember as a group. Chunks embrace both RDF triples and Property Graphs. For more information on chunks and rules see:
> 
>  https://www.w3.org/Data/demos/chunks/chunks.html <https://www.w3.org/Data/demos/chunks/chunks.html>
>  https://www.w3.org/Data/events/tpac2019/digital-transformation.pdf <https://www.w3.org/Data/events/tpac2019/digital-transformation.pdf>
> 
> This may be the wrong list to ask for these, but in general, collecting challenges for researchers to gauge progress against would be really helpful for driving progress, and help to evaluate which approaches are more effective.
> 
> I am interested in use cases and datasets suitable for use in work on, e.g.
> 
> Unsupervised learning of taxonomies and ontologies from noisy data
> Reinforcement learning of skills in simulated environments
> Causal reasoning, for planning actions or explaining faults
> 
> Note that I am currently working on a demo featuring autonomous driving as a simulated environment that will allow me to explore how different cognitive tasks can coexist on the same rule engine and work together in a timely way. In principle, this could be extended to support reinforcement learning scenarios.
> 
> Dave Raggett <dsr@w3.org <mailto:dsr@w3.org>> http://www.w3.org/People/Raggett <http://www.w3.org/People/Raggett>
> W3C Data Activity Lead & W3C champion for the Web of things 
> 
> 
> 

Dave Raggett <dsr@w3.org> http://www.w3.org/People/Raggett
W3C Data Activity Lead & W3C champion for the Web of things