Steady-state simulation of queueing processes: survey of problems and solutions
ACM Computing Surveys (CSUR)
Likelihood ratio gradient estimation for stochastic systems
Communications of the ACM - Special issue on simulation
Efficient estimation of cell blocking probability for ATM systems
IEEE/ACM Transactions on Networking (TON)
Simulation optimization: methods and applications
Proceedings of the 29th conference on Winter simulation
A simple approximation to minimum-delay routing
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Control variate models for sensitivity estimates of repairable item systems
WSC '87 Proceedings of the 19th conference on Winter simulation
Likelilood ratio gradient estimation: an overview
WSC '87 Proceedings of the 19th conference on Winter simulation
Pertubation analysis—theoretical, experimental, and implementational aspects
WSC '87 Proceedings of the 19th conference on Winter simulation
Future directions in response surface methodology for simulation
WSC '87 Proceedings of the 19th conference on Winter simulation
On the sensitivity analysis of the expected accumulated reward
Performance Evaluation
Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation
The Journal of Machine Learning Research
Policy Gradient in Continuous Time
The Journal of Machine Learning Research
Geometric variance reduction in Markov chains: application to value function and gradient estimation
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Infinite-horizon policy-gradient estimation
Journal of Artificial Intelligence Research
Sensitivity analysis and the “what if” problem in simulation analysis
Mathematical and Computer Modelling: An International Journal
Generalized estimates for performance sensitivities of stochastic systems
Mathematical and Computer Modelling: An International Journal
Estimates and confidence intervals for importance sampling sensitivity analysis
Mathematical and Computer Modelling: An International Journal
Techniques for simulation response optimization
Operations Research Letters
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We present a new method of obtaining derivatives of expectations with respect to various parameters. For example, if &lgr; is the rate of a Poisson process, NT is the number of Poisson events in (0, T),and &psgr; is nearly any function of the sample path (e.g. a performance measure in a queuing network), then we show that d/d&lgr; E&lgr;(&psgr;) = E&lgr; ((NT/&lgr; - T)&psgr;), which yields an obvious algorithm. We have proven that the method works for a wide class of parameters and performance measures in regenerative simulation. We also report on the method's limitations and on some numerical experiments.