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Friday, July 31, 2020 | History

4 edition of The automation of syllotistic. II. Optimization and complexity issues. found in the catalog.

The automation of syllotistic. II. Optimization and complexity issues.

by D. Cantone

  • 391 Want to read
  • 21 Currently reading

Published by Courant Institute of Mathematical Sciences, New York University in New York .
Written in English


Edition Notes

StatementBy D. Cantone, E.G. Omodeo, A. Policriti.
ContributionsOmodeo, E., Policriti, A.
The Physical Object
Pagination19 p.
Number of Pages19
ID Numbers
Open LibraryOL17976827M

Complexity theory is the appropriate setting for the study of such problems. It is also the home of one of the most fundamental open problems in mathematics, namely the famous NP versus P problem. Some 40 years after the discovery of this problem, complexity theory has matured into an extremely rich and fasci-File Size: KB.   Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications presents the latest research trends and developments in the area of applied optimization methodologies and soft computing techniques for solving complex problems. Taking a multi-disciplinary approach, this critical publication is an essential reference.

The book may be used as a text for a theoretical convex optimization course; the author has taught several variants of such a course at MIT and elsewhere over the last ten years. It may also be used as a supplementary source for nonlinear programming classes, and as a theoretical foundation for classes focused on convex optimization models. Optimization, Complexity and Invariant Theory. Date and location: June , , Institute for Advanced Study, Princeton, NJ USA. Organizer: Avi Wigderson. Links to the recorded lectures can be found on the Agenda page.

II. Preface Complexit y Theory is a cen tral eld of Theoretical Computer Science, with remark able list celebrated ac hiev emen ts as w ell as a v ery vibran t presen t researc h activit y. The eldis concerned with the study of intrinsic complexit y computational tasks, and this tend to aim at gener ality: It fo cuses on natural computational File Size: 2MB. rated book of D. A. Wismer and R. Chattergy (), which served to introduce the topic of nonlinear optimization to me many years ago, and which has more than casually influenced this work. With so many excellent texts on the topic of mathematical optimization available, the question can justifiably be posed: Why another book andFile Size: 1MB.


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