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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | L'Ecuyer, Pierre |
| Copyright Year | 2015 |
| Description | Author affiliation: Universite de Montreal, C.P. 6128, Succ. Centre-Ville, DIRO, Quebec H3C 3J7, CANADA (L'Ecuyer, Pierre) |
| Abstract | In stochastic simulation, we construct mathematical models to imitate the behavior of real systems, use computers to sample behavioral histories (sample paths) of these models, and exploit those samples to improve decision making with the real system. The imitation part can be very challenging, in particular for modeling uncertainty. Fitting univariate probability distribution to data is far from sufficient. Modeling the dependence is very important and much more challenging. It involves multivariate distributions, copulas, stochastic processes, and other complicated stochastic objects. Simulating the model on a computer also involves an imitation game, to simulate the realizations of random variables and stochastic processes with deterministic algorithms on a computer. Random number generation involves writing deterministic computer programs that can imitate simple probabilistic models such as independent uniform random variables uniformly distributed over the interval (0, 1). An “exact” algorithmic implantation of such models is theoretically impossible, so we settle for a reasonable fake. The talk will give snapshots and expose ideas collected from the author's journey thought stochastic simulation. The tour will start with random number generation and visit some challenging problems such as stochastic modeling, simulation-based optimization, rare events, simulation on parallel processors, and future challenges. |
| Starting Page | 1867 |
| Ending Page | 1867 |
| File Size | 85933 |
| Page Count | 1 |
| File Format | |
| ISSN | 15584305 |
| e-ISBN | 9781467397438 |
| DOI | 10.1109/WSC.2015.7408303 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-12-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computational modeling Stochastic processes Mathematical model Computers Random variables Random number generation Biological system modeling |
| Content Type | Text |
| Resource Type | Article |
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