Re: unboxed structure fields (or class slots)
"David McClain (as dbm at refined-audiometrics dot com)" <[email protected]>
| Newsgroups | gmane.lisp.lispworks.general |
|---|---|
| Message-ID | <[email protected]> |
>> We also used Probabilistic Neural Networks to build target trackers for search and destroy missions - LIDAR underwater mine detection systems, and EKV Kinetic Kill Vehicles for taking out incoming nuclear warheads. > > I did some work with HRL a dozen or so years back to use first-order logic functions to represent probabilities (e.g. confidence), so you could do probabilistic (adversarial) planning without actually having to deal with the math, after giving up on using MDPs. More qualitative than quantitative. The more interesting part of the research dealt with autoepistemic logic, so the system could reason about what it didn’t know and then create plans to find out to reduce uncertainty. Sorry, when I stated “Probabilistic NNs” I meant that the networks used an exponential as the decision function chaining to the next layer, instead of a sigmoid. That exponential yields a NN that acts similar to a Kth nearest neighbor recognizer. This was originally developed at Lockheed, and then we adapted for our use on our airborne LIDAR underwater mine detection system. _______________________________________________ Lisp Hug - the mailing list for LispWorks users [email protected] http://www.lispworks.com/support/lisp-hug.html