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SPSC: a new execution policy for exploring discrete-time stochastic simulations

2019/09/20 by Huang, Yu-Lin, Gildąs Morvan, Morvan, Gildas +3
Computer Science · Decision Sciences · Mathematics · #FOS: Computer and information sciences #Modeling and Simulation Systems #Modeling, Simulation, and Optimization #Multiagent Systems (cs.MA) #Performance (cs.PF) #Simulation Techniques and Applications

paper · pdf · doi:10.48550/arxiv.1909.09390

openalex publication_date 2019/09/20 · openalex created_date 2019/09/26 · openalex updated_date 2026/07/28

Abstract

In this paper, we introduce a new method called SPSC (Simulation, Partitioning, Selection, Cloning) to estimate efficiently the probability of possible solutions in stochastic simulations. This method can be applied to any type of simulation, however it is particularly suitable for multi-agent-based simulations (MABS). Therefore, its performance is evaluated on a well-known MABS and compared to the classical approach, i.e., Monte Carlo.

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