New Article, shorttitstring

JAIR is pleased to announce the publication of the following article:

Finkelstein, L., Markovitch, S. and Rivlin, E. (2003)
  "Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared 
Resources", 
   Volume 19, pages 73-138.

   For quick access via your WWW browser, use this URL:
     http://www.jair.org/abstracts/finkelstein03a.html

Abstract:
The performance of anytime algorithms can be improved by
simultaneously solving several instances of algorithm-problem
pairs. These pairs may include different instances of a problem (such
as starting from a different initial state), different algorithms (if
several alternatives exist), or several runs of the same algorithm
(for non-deterministic algorithms). In this paper we present a
methodology for designing an optimal scheduling policy based on the
statistical characteristics of the algorithms involved. We formally
analyze the case where the processes share resources (a
single-processor model), and provide an algorithm for optimal
scheduling.  We analyze, theoretically and empirically, the behavior
of our scheduling algorithm for various distribution types.  Finally,
we present empirical results of applying our scheduling algorithm to
the Latin Square problem. 

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        ftp://ftp.cs.cmu.edu/project/jair/volume19/finkelstein03a.ps
    The compressed PostScript file is named finkelstein03a.ps.Z 

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-- 
Steven Minton
JAIR Managing Editor