Intelligence Semantics

Parallelism and Programming in Classifier Systems by Stephanie Forrest

By Stephanie Forrest

Parallelism and Programming in Classifier structures bargains with the computational houses of the underlying parallel laptop, together with computational completeness, programming and illustration strategies, and potency of algorithms. particularly, effective classifier process implementations of symbolic information buildings and reasoning strategies are provided and analyzed intimately.
The ebook exhibits how classifier structures can be utilized to enforce a suite of beneficial operations for the category of data in semantic networks. A subset of the KL-ONE language was once selected to illustrate those operations. particularly, the approach plays the subsequent projects: (1) given the KL-ONE description of a selected semantic community, the method produces a collection of creation ideas (classifiers) that symbolize the community; and (2) given the outline of a brand new time period, the process determines the correct place of the hot time period within the present community. those elements of the procedure are defined intimately. The implementation unearths yes computational houses of classifier platforms, together with completeness, operations which are rather common and effective, and people who are really awkward. The publication indicates how high-level symbolic buildings might be outfitted up from classifier structures, and it demonstrates that the parallelism of classifier structures should be exploited to enforce them successfully. this can be major due to the fact classifier platforms needs to build huge subtle types and cause approximately them in the event that they are to be really ""intelligent.""
Parallel businesses are of curiosity to many parts of computing device technology, akin to specification, programming language layout, configuration of networks of separate machines, and synthetic intelligence This e-book concentrates on a specific form of parallel association and a specific challenge within the sector of AI, however the ideas which are elucidated are appropriate within the wider atmosphere of laptop technology.

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Even though the complexity of complete classification has been studied extensively, these results are not directly applicable to the incomplete algorithms that are used in practice. In addition, small differences in the language can have an enormous effect on the complexity of the algorithms (see [17]). The details of this analysis appear in Chapter 6. 3 Summary In summary, this research demonstrates the feasibility of a parallel classification algo­ rithm for KL-ONE by constructing an implementation of one.

The paper also describe a formal classification procedure that is provably sound (but not complete). While the results of this paper are of general interest, this is not the best introduction to KL-ONE. The 1985 review article in Cognitive Science, however, does provide a good description of KL-ONE and is intended for the general reader [19]. It explains how the various implementation projects have fit into the overall KL-ONE philosophy. More recently, research on KL-ONE-like languages has followed two major themes: investigating the relation between expressive power and complexity of subsumption op­ erations [17,84,94], and building implementations.

In this case the role, Sibling, is a defining property of PersonWithOnlySisters. This is indicated in a graph representation by a line segment connecting the concept with the role. Value restrictions are indicated with a single arrow from the role to the value restriction (a concept). 4 illustrates these conventions. 4 Value Restrictions It should be noted that this definition does not require a PersonWithOnlySisters to actually have any siblings. It just says that if there are any, they must be female.

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