2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation (2009)
Lake Placid, New York, USA
June 22, 2009 to June 25, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PADS.2009.11
Simulation replication is a necessity for all stochastic simulations. Its efficient execution is particularly important when additional techniques are used on top, such as optimization or sensitivity analysis. One way to improve replication efficiency is to ensure that the best configuration of the simulation system is used for execution. A selection of the best configuration is possible when the number of required replications is sufficiently high, even without any prior knowledge on simulator performance or problem instance. We present an adaptive replication mechanism that combines portfolio theory with reinforcement learning: it adapts itself to the given problem instance at runtime and can be restricted to an efficient algorithm portfolio.
Simulation Replication, Algorithm Selection, James II
S. Leye, R. Ewald and A. M. Uhrmacher, "An Efficient and Adaptive Mechanism for Parallel Simulation Replication," 2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation(PADS), Lake Placid, New York, USA, 2009, pp. 104-113.