Blind Simulation and Regenerative Processes

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ABSTRACT: NCR-9505443, University of Wisconsin-Madison, Blind Simulation and Regenerative Processes, PI-James A. Bucklew and Peter E. Ney: Importance sampling is used to speed up Monte Carlo simulation of rare events. The methods used to date have required exact knowledge of the underlying probability structure of the system being simulated. Direct Monte Carlo simulation requires only an assumption of ergodicity to guarantee that relative frequency estimates of system parameters will converge to true values. The direct Monte Carlo technique is an example of a blind simulation technique: a generic class of methodologies which bootstrap their way without exact knowledge of the underlying probability law. Some partial results achieved to date indicate that in many interesting situations, blind techniques can perform just about as well as those utilizing much more prior information. Applied to systems with memory (Markovian for example) these techniques lead naturally to the study of regenerative processes. These are processes that at random times stop and essentially start themselves over again. Aspects of the theory of these processes are yet to be developed and are needed for the analysis of blind simulation methods. This study of blind simulation and regenerative processes promises to very important in the bag of tricks available to system simulators.***************************************************************************** Aubrey M. BushProgram Director, Acting Deputy Divison DirectorDivision of Networking and Communica tions Research and InfrastructureNational Science Foundation