基于图形的人类行为模拟数据分析

Ales Tavcar, M. Gams, M. Kvassay, M. Laclavik, L. Hluchý, B. Schneider, H. Bracker
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引用次数: 4

摘要

在本文中,我们描述了我们目前正在进行的工作,我们展示了基于图形的方法分析计算机模拟人类行为数据的潜力和普遍性。第一种方法是MASDA算法,通过本体驱动的抽象过程分析行动序列,旨在以图形化和符号化的形式分离战略序列和战略行动描述。第二种方法是基于扩散激活算法,旨在寻找仿真结果与其各种内部参数、设置、事件和实体之间的显著相关性。我们在EDA项目A-0938-RT-GC EUSAS的背景下说明了我们的方法,这些方法将在验证后使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Graph-based analysis of data from human behaviour simulations
In this article, which describes our current work in progress, we demonstrate the potential and universality of graph-based methods for analysing data from computer simulations of human behaviour. The first method, MASDA algorithm, analyses action sequences through an ontology-driven process of abstraction, and aims at isolating strategic sequences and strategic action descriptions in a graphical and symbolic form. The second method, based on the spreading activation algorithm, aims at finding significant correlations between the simulation results and its various internal parameters, settings, events and entities. We illustrate our methods in the context of the EDA project A-0938-RT-GC EUSAS, where they are to be used after validation.
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