Titlebook: Learning and Reasoning with Complex Representations; PRICAI‘96 Workshops Grigoris Antoniou,Aditya K. Ghose,Miros?aw Truszcz Conference pro

冷漠

rheumatism

儀式

lymphoma

cringe

Bravura

The role of default representations in incremental learning,g an operator which is provably minimal even in the case of iterated sequences of specializations. The operator also benefits from the advantages of lazy evaluation and deferred choice. Second, it provides a semantic basis for inducing default theories and presents an incremental learning algorithm

Apraxia

Learning stable concepts in a changing world,formance. Existing machine learning approaches to this problem use an incremental learning, on-line paradigm. Batch, off-line learners tend to be ineffective in domains with hidden changes in context as they assume that the training set is homogeneous..We present an off-line method for identifying h

dowagers-hump

Extort

Induction of constraint logic programs, Programming (LP) language. The application of ILP to problems involving numerical information has shown the need for basic numerical background knowledge (e.g. relation “l(fā)ess than”). Our thesis is that one should rather choose Constraint Logic Programming (CLP) as the representation language of hyp

拾落穗