Enhancement of Decision Strategies Selection Under Uncertainty Using Discrete Simulation

We want via this paper to show effectiveness of Discrete Simulation (DS) paradigm to improve and enhance Uncertain Decision Making. Our main goal is to allow modeling and simulation of Decision-making problems under uncertainty. Our simulation system implements two DS techniques: First order Simulation and second order simulation (characterized by its population size and number of replications). We propose in this paper to adapt simulation routines of these two techniques to the principles of decision tree representation formalism, to implement a forward inference mechanism that allows optimal decision strategy determination under uncertainty. Several comparative tests of the proposed simulation techniques with mathematical measurements have been done. Our system allows multiple types of users (Decision makers, analysts, students,...) to create Decision models, access to existing models, run simulations, compare measures and share experiences. All created models and calculated measures are saved in XML format to permit their easy reuse.