Slides available from KGC-2022 workshop on imperfect knowledge

We are always learning and never attain perfect knowledge. Our reasoning out of necessity has to deal with uncertain, incomplete and inconsistent knowledge. Traditional logic is ill-suited to this, and statistical approaches often have practical difficulties with obtaining the statistics. Qualitative approaches on the other hand are well suited to consideration of multiple lines of argument for and against a premise, including many forms of plausible reasoning such as analogical, causal, social, etc.

The slides for all of the talks are linked from the GitHub web page for the workshop on representing and reasoning with imperfect knowledge, part of the Knowledge Graph conference (KGC-2022), see:

https://www.knowledgegraph.tech/kgc-2022-workshop-representing-and-reasoning-with-imperfect-knowledge/ <https://www.knowledgegraph.tech/kgc-2022-workshop-representing-and-reasoning-with-imperfect-knowledge/> 

We are now starting to plan for organising a longer and free-to-attend online workshop later this year.

p.s. I am progressing my plausible reasoning demo and hope to extend it considerably over the summer, before starting work on integrating support for System 1 and 2 thinking.

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