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Comparison of crisp systems and fuzzy systems in agent-based simulation: A case study of soccer penalties

机译:基于主体的仿真中的清脆系统与模糊系统的比较:以足球点球为例

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The Belief-Desire-Intention (BDI) software model is an example of a reasoning architecture for a bounded rational software agent. In our research we plan to expand the application of the BDI software model to the area of simulating human behaviour in social and socio-technical systems. To this effect, in this paper we explore the differences in using a classical crisp rule-based approach and a fuzzy rule-based approach for the reasoning within the BDI system. As a test case we have chosen a football penalty shootout. We have kept the case study example deliberately simple so that we can focus on the effects the different BDI implementations have on the decisions made. Our experiments highlight that the crisp system can result in unwanted “preferred” actions because of sudden leaps or drops between different ranges of decision variables, while the fuzzy system results have smoother transitions which results in more consistent decisions. The behaviour, as showcased in this simple context, underlines that a change from crisp to fuzzy rule based systems as the underlying reasoning model in BDI systems can provide the path to a superior approach for the simulation of human behaviour, which we will explore further in the future.
机译:Belief-Desire-Intention(BDI)软件模型是有限理性软件代理的推理体系结构的示例。在我们的研究中,我们计划将BDI软件模型的应用扩展到模拟社会和社会技术系统中人类行为的领域。为此,在本文中,我们探讨了在BDI系统中使用经典的基于明晰规则的方法和基于模糊规则的方法进行推理的区别。作为测试案例,我们选择了足球点球大战。我们故意使案例研究示例保持简单,以便我们可以集中精力研究不同BDI实现对决策的影响。我们的实验强调,由于决策变量在不同范围之间突然跳跃或下降,因此清晰的系统可能导致不必要的“首选”操作,而模糊系统的结果具有更平滑的过渡,从而导致决策更加一致。如在此简单上下文中所展示的,该行为强调了从脆性到基于模糊规则的系统的变化,作为BDI系统中的基础推理模型,可以为模拟人类行为提供更好的方法,我们将在下文中进一步探讨。未来。

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