Optimistic parallel simulation engine for predicting future situations incorporating observation data

Abstract

Coping with emergency situations requires effective and prompt decision-making under constantly changing situations. The deployment of various kinds of sensors makes it possible to acquire vast amounts of information. At present, however, most information processing is not automated; therefore, the quality of decision-making depends heavily on the capacities of the decision maker. To solve this problem, we propose a system for predicting future situations through parallel simulations based on observation data. To facilitate the development of such systems, we have been developing an optimistic simulation engine (hereafter referred to as O-SE) that supports parallel simulation of many possible situations and dynamic simulation modification based on observation data acquired by sensors. The design and evaluation results of the O-SE are illustrated in this paper.