High-Speed Generation of Goal-Oriented Scenarios Using Bidirectional Combination of Effect Propagation on a Qualitative and Quantitative Hybrid Model

摘要

This paper addresses the high-speed generation of goal-oriented scenarios on a qualitative and quantitative hybrid model. The goal-oriented scenarios can be generated efficiently by a bidirectional combination of forward propagation and backward propagation, if differences between the values related to each scenario are small on a certain time step. Thus, the method combines the scenarios when each value can be regarded as the same from qualitative value viewpoints. Furthermore, the proposed method decides the number of both propagations to generate the required number of goal-oriented scenarios while decreasing the number of time-consuming backward propagations. Experimental results show that the computational time for generating the required number of goal-oriented scenarios is decreased by 98% compared to solely forward propagation.