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Homogeneous Ordered Graphs, Metrically Homogeneous Graphs, and Beyond: Volume 1, Ordered Graphs and Distanced Graphs
Hardback
Main Details
Title |
Homogeneous Ordered Graphs, Metrically Homogeneous Graphs, and Beyond: Volume 1, Ordered Graphs and Distanced Graphs
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Authors and Contributors |
By (author) Gregory Cherlin
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Series | Lecture Notes in Logic |
Physical Properties |
Format:Hardback | Pages:386 | Dimensions(mm): Height 235,Width 157 |
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ISBN/Barcode |
9781009229692
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Classifications | Dewey:511.5 |
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Audience | |
Illustrations |
Worked examples or Exercises
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Publishing Details |
Publisher |
Cambridge University Press
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Imprint |
Cambridge University Press
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Publication Date |
7 July 2022 |
Publication Country |
United Kingdom
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Description
This is the first of two volumes by Professor Cherlin presenting the state of the art in the classification of homogeneous structures in binary languages and related problems in the intersection of model theory and combinatorics. Researchers and graduate students in the area will find in these volumes many far-reaching results and interesting new research directions to pursue. In this volume, Cherlin develops a complete classification of homogeneous ordered graphs and provides a full proof. He then proposes a new family of metrically homogeneous graphs, a weakening of the usual homogeneity condition. A general classification conjecture is presented, together with general structure theory and applications to a general classification conjecture for such graphs. It also includes introductory chapters giving an overview of the results and methods of both volumes, and an appendix surveying recent developments in the area. An extensive accompanying bibliography of related literature, organized by topic, is available online.
Author Biography
Gregory Cherlin is Distinguished Professor Emeritus at Rutgers University. He has worked on applications of model theory to algebra and combinatorics for half a century, and has published four books and over 100 articles on model theory and its applications.
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