Non-cumulative learning in METAXA3
Werner Emde · 1987
emde%dbOtuil1.bitnetGwiscvm.wise.edu Knowledge revision in incremental learning systems will usually be restricted by some external criteria to achieve a conservative behavior of the system. Unfortunately, conservatism has some well known drawbacks. Therefore, it can become necessary to drop these restrictions and to change over to a non-cumulative learning mode. In this paper the incremental learning system METAXA.3 is described which is able to perform a special kind of noncumulative knowledge revision enabling it to learn without requiring unrestricted resources or the absence of noisy data. The generalization approach is sketched and knowledge revision in METAXA.3 is described. I