基于agent的仿真中清晰系统与模糊系统的比较——以足球判罚为例

T. Vu, Peer-Olaf Siebers, Christian Wagner
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引用次数: 7

摘要

信念-欲望-意图(BDI)软件模型是有界理性软件代理的推理体系结构的一个示例。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的人类行为领域。为此,本文探讨了在BDI系统中使用经典的基于清晰规则的方法和基于模糊规则的方法进行推理的差异。作为一个测试案例,我们选择了一个足球点球大战。我们故意使案例研究示例保持简单,以便我们可以专注于不同的BDI实现对所做决策的影响。我们的实验强调,由于不同范围的决策变量之间的突然跳跃或下降,清晰系统可能导致不必要的“首选”行为,而模糊系统结果具有更平滑的过渡,从而导致更一致的决策。在这个简单的环境中所展示的行为,强调了从清晰到模糊基于规则的系统作为BDI系统的底层推理模型的变化,可以为模拟人类行为提供一种优越的方法,我们将在未来进一步探索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of crisp systems and fuzzy systems in agent-based simulation: A case study of soccer penalties
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.
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