Overview
- Proposes the use of representation theorems as a means to develop an understanding of all models of a given specification
- Demonstrates the application of the general methodology with examples in qualitative spatial reasoning, data stream processing, and belief revision
- Provides the basis for the development of toolkits that support application designers with automatically built representations
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Table of contents (8 chapters)
Keywords
About this book
For qualitative spatial reasoning, it develops a model of spatial relatedness that captures the scaling context with hierarchical partitions of a spatial domain, and axiomatically characterizes the resulting relations. It also shows that various important properties of stream processing, such as prefix-determinedness or various factorization properties can be axiomatized, and that the axioms are fulfilled by natural classes of stream functions. The third example is belief revision, which is concerned with the revision of knowledge bases under new, potentially incompatible information. In this context, the book considers a subclass of revision operators, namely the class of reinterpretation operators, and characterizes them axiomatically. A characteristic property of reinterpretation operators is that of dissolving potential inconsistencies by reinterpreting symbols of the knowledge base.
Intended for researchers in theoretical computer science or one of the above application domains, the book presents results that demonstrate the use of representation theorems for the design and evaluation of formal specifications, and provide the basis for future application-development kits that support application designers with automatically built representations.
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Bibliographic Information
Book Title: Representation Theorems in Computer Science
Book Subtitle: A Treatment in Logic Engineering
Authors: Özgür Lütfü Özçep
DOI: https://doi.org/10.1007/978-3-030-25785-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-25784-2Published: 07 August 2019
Softcover ISBN: 978-3-030-25787-3Published: 14 August 2020
eBook ISBN: 978-3-030-25785-9Published: 16 July 2019
Edition Number: 1
Number of Pages: XIV, 190
Topics: Theory of Computation, Logic in AI, Data Mining and Knowledge Discovery, Information Storage and Retrieval