[EMAIL PROTECTED] wrote:
[EMAIL PROTECTED] wrote:
There are things you can do. remove the agenda, but make sure all node
memories are iterated in lifo order - thus propagations will happen in
approximate lifo, but fire straight away. Make sure the network building
orders according to salience. You can then do an adapter algorithm that
chooses to store or not store partial matches, based on demands of the
problem. It isn't hard to write a network that can lazily pull all the
joins from parent nodes (ala leaps) if there are no partial matches -
thus creating a hybrid algorithm.
Thank you very much for your fast reply, it helps a lot!
If it causes not too much trouble and you find time for this, I would like to
ask you if you have more information (weblinks, reports, etc.) on these
algorithms or their implementations and commercial use.
Just use google scholar search. KBSC also have a page of links to useful
papers:
http://kbsc.com/aibooks.html
It's quite hard to find recent reports (or reports at all), it seems all the
theoretical work has been done long ago and further development only happens in
commercial products.
Yes it seems all the interesting research was done in the 90s and then
it just stops. This is partly due to the commercialisation of production
systems and partly due to academia only being interested in prolog
engines. While production engines have the performance, which business
are interested in, academia go for prolog which they can do complete
proofs in, so their research is focused there.
Thank you very much!
Regards, E.L.
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