KL-ONE lets one define and use a class of descriptive terms called Concepts, where each Concept denotes a set of objects A subsumption relation between Concepts is defined which is related to set inclusion by way of a semantics for Concepts. This subsumption relation defines a partial order on Concepts, and KL-ONE organizes all Concepts into a taxonomy that reflects this partial order. Classification is a process that takes a new Concept and determines other Concepts that either subsume it or that it subsumes, thereby determining the location for the new Concept within a given taxonomy. We discuss these issues and demonstrate some uses of the classification algorithm.

to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity

will incorporate a theoretically justi ed representation of the native speaker's linguistic knowledge (a grammar) as a component separate both from the computational mechanisms that operate on it (a processor) and from other nongrammatical processing parameters that might influence the processor

This reprint version is almost identical to the book. The page numbering is different, the format of the bibliography differs from the book and the reprint version does not contain an author index. Otherwise the contents is the same, however.

Disjunctive Logic Programming (DLP) is an advanced formalism for knowledge representation and reasoning, which is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class ΣP 2 (NPNP). Thus, under widely

considered the special case where D is an overcomplete system consisting of exactly two orthobases, and has shown that, under a condition of mutual incoherence of the two bases, and assuming that S has a sufficiently sparse representation, this representation is unique and can be found by solving a convex

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Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllable-oriented continuous speech recognition system. The vocabulary in-cluded many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain

To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations

the possibility of stable recovery under a combination of sufficient sparsity and favorable structure of the overcomplete system. Considering an ideal underlying signal that has a sufficiently sparse representation, it is assumed that only a noisy version of it can be observed. Assuming further