Probabilistic methods in Computer Science range from design of algorithms to analysis of typical behavior of algorithms to proving lower bounds in complexity theory. This research will concentrate on a number of specific problems where application of the probabilistic method seems promising. The questions include graph algorithms (finding approximation algorithms for the coloring problem and the independent set size problem), parallel sorting (in the so-called PRAM model), as well as algebraic questions (diameter of Cayley graphs), problems in circuit complexity (non-linear lower bounds), and complexity of on-line algorithms. Based on past experience, the asymptotic combinatorial tools are expected to be applicable more broadly, beyond the problems stated.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Communication Foundations (CCF)
Application #
9200788
Program Officer
Dana May Latch
Project Start
Project End
Budget Start
1992-09-01
Budget End
1996-02-29
Support Year
Fiscal Year
1992
Total Cost
$242,678
Indirect Cost
Name
Rutgers University
Department
Type
DUNS #
City
New Brunswick
State
NJ
Country
United States
Zip Code
08901