Using NN-DEVS Approach for Modelling and Simulation of Imperfect Systems: Application to the Reactive Navigation of Autonomous Robot

Kadda Mostefaoui, Y. Dahmani, B. Mebarek, Mohamed Goucem
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Abstract

In this paper, we are interested in the modelling and simulation of imperfect systems in the DEVS context. We want to hybrid the DEVS formalism with artificial neural networks and to propose a new modelling and simulation approach which makes it possible to represent the behavior of imperfect systems. The problematic of our work is the integration into the DEVS formalism of tools from artificial intelligence allowing the representation, manipulation, and processing of imperfect data (imprecise, uncertain). NN-DEVS is a new hybrid approach which allows to extend the classic DEVS formalism. This new approach is effective in uncertain systems where the behavior of the system is stochastic. To validate the proposed NN-DEVS approach, we apply this approach to a complex reactive navigation system of a mobile robot.
基于NN-DEVS方法的不完全系统建模与仿真:在自主机器人响应式导航中的应用
在本文中,我们对DEVS环境中不完善系统的建模和仿真感兴趣。我们希望将DEVS形式化与人工神经网络相结合,并提出一种新的建模和仿真方法,使其能够表示不完美系统的行为。我们工作的问题在于将人工智能工具整合到DEVS的形式化中,允许对不完美数据(不精确、不确定)进行表示、操作和处理。NN-DEVS是一种新的混合方法,它允许扩展经典DEVS的形式主义。该方法在系统行为为随机的不确定系统中是有效的。为了验证所提出的NN-DEVS方法,我们将该方法应用于移动机器人的复杂响应式导航系统。
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