<p>Detailed Description</p> <ul> <li>A selection of up-to-date contributions in group theory and its relations with logic and cryptography</li> <li>Includes works by well-known experts in the field</li> <li>Of interest to mathematicians working in group theory and related areas</li></ul>
Complexity and Randomness in Group Theory
β Scribed by Frederique Bassino, Ilya Kapovich, Markus Lohrey, Alexei Miasnikov, Cyril Nicaud, Andrey Nikolaev, Igor Rivin, Vladimir Shpilrain, Alexander Ushakov, Pascal Weil
- Publisher
- De Gruyter
- Year
- 2020
- Tongue
- English
- Leaves
- 387
- Series
- Gagta Book, 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book shows new directions in group theory motivated by computer science. It reflects the transition from geometric group theory to group theory of the 21st century that has strong connections to computer science. Now that geometric group theory
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<p>Detailed Description</p> <ul> <li>A selection of up-to-date contributions in group theory and its relations with logic and cryptography</li> <li>Includes works by well-known experts in the field</li> <li>Of interest to mathematicians working in group theory and related areas</li></ul>
<p>This book contains a revised version of the dissertation the author wrote at the Department of Computer Science of the University of Chicago. The thesis was submitted to the Faculty of Physical Sciences in conformity with the requirements for the PhD degree in June 1999. It was honored with the 1
<p>This book contains a revised version of the dissertation the author wrote at the Department of Computer Science of the University of Chicago. The thesis was submitted to the Faculty of Physical Sciences in conformity with the requirements for the PhD degree in June 1999. It was honored with the 1
<p>One of the most important and successful theories in computational complexΒ ity is that of NP-completeness. This discrete theory is based on the Turing machine model and achieves a classification of discrete computational probΒ lems according to their algorithmic difficulty. Turing machines forma
<p>Intuitively, a sequence such as 101010101010101010β¦ does not seem random, whereas 101101011101010100β¦, obtained using coin tosses, does. How can we reconcile this intuition with the fact that both are statistically equally likely? What does it mean to say that an individual mathematical object su