000 02196cam a2200229 i 4500
005 20240325175359.0
008 150814s2016 enka b 001 0 eng
020 _a9781107118508
041 _aeng
082 0 0 _a511.5
_bFriI
100 1 _aFrieze, Alan
245 1 0 _aIntroduction to Random Graphs /
_cAlan Frieze and Michał Karoński
260 _aCambridge :
_bCambridge University Press,
_cc2016.
300 _axvii, 464p.
505 8 _aMachine generated contents note: Preface; Part I. Basic Models: 1. Random graphs; 2. Evolution; 3. Vertex degrees; 4. Connectivity; 5. Small subgraphs; 6. Spanning subgraphs; 7. Extreme characteristics; 8. Extremal properties; Part II. Essential Model Extensions: 9. Inhomogeneous graphs; 10. Fixed degree sequence; 11. Intersection graphs; 12. Digraphs; 13. Hypergraphs; Part III. Other Models: 14. Trees; 15. Mappings; 16. k-out; 17. Real-world networks; 18. Weighted graphs; 19. Brief notes on uncovered topics; Part IV. Tools and Methods: 20. Moments; 21. Inequalities; 22. Differential equations method; 23. Branching processes; 24. Entropy; References; Author index; Main index.
520 _a"From social networks such as Facebook, the World Wide Web and the Internet, to the complex interactions between proteins in the cells of our bodies, we constantly face the challenge of understanding the structure and development of networks. The theory of random graphs provides a framework for this understanding, and in this book the authors give a gentle introduction to the basic tools for understanding and applying the theory. Part I includes sufficient material, including exercises, for a one semester course at the advanced undergraduate or beginning graduate level. The reader is then well prepared for the more advanced topics in Parts II and III. A final part provides a quick introduction to the background material needed. All those interested in discrete mathematics, computer science or applied probability and their applications will find this an ideal introduction to the subject"--
650 0 _aRandom Graphs
650 0 _aCombinatorial Probabilities
650 0 _aProbabilities
700 1 _aKaroński, Michał
942 _cBK
999 _c5673
_d5673