Some representational issues in default reasoning

Representational Issues in Meta-Learning

To address the problem of algorithm selection for the classification task, we equip a relational case base with new similarity measures that are able to cope with multirelational representations. The proposed approach builds on notions from clustering and is closely related to ideas developed in similarity-based relational learning. The results provide evidence that the relational representatio...

Default Reasoning in CHR∨

CHR∨ has emerged as a versatile knowledge representation language, usable for an unparalleled variety of automated reasoning tasks: constraint solving, optimization, classification, subsumption, classical deduction, abduction, truth-maintenance, belief revision, belief update and planning. In this paper, we add default reasoning to this list, by showing how to represent default logic theories i...

Representational Issues within Eurotra

Machine translation of subordinate clauses, whether finite or non-finite, poses a series of problems within representational issues. In £ U R O T R A this subject has recently been investigated for complements as well as for modifiers to verbal, nominal, adjectival, and prepositioned heads. Some of the problems encountered during these investigations will be addressed in this paper, with a part...

What Should Default Reasoning Be, by Default?

This is a position paper concerning the role of empirical studies of human default reasoning in the formalization of AI theories of default reasoning. We note that AI motivates its theoretical enterprise by reference to human skill at default reasoning, but that the actual research does not make any use of this sort of information and instead relies on intuitions of individual investigators. We...

Computing Speciicity in Default Reasoning