Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
We present an in-kernel disk prefetcher which uses speculative execution to determine what data an application is likely to require in the near future. By placing our design withi...
This paper presents the analysis of the optimization for the production of precast pieces in a workshop with the help of simulation to obtain several working alternatives. The mai...
Deformable models are an attractive approach to recognizing nonrigid objects which have considerable within class variability. However, there are severe search problems associated...
Christopher K. I. Williams, Michael Revow, Geoffre...
We present a methodology for using analogy to derive programs based on a derivational transformation method. The derived programs are deductively closed under the rules in the kno...