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Event-Based Life in a Nutshell: How Evaluation of Individual Life Cycles Can Reveal Statistical Inferences Using Action-Accumulating P Systems

机译:基于事件的寿命,简称:如何使用动作累积P系统揭示统计推论的评估

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A sequence of perceivable events or recorded observations over time commonly witnesses the life cycle of an individual at a macroscopic perspective. In case of a human being, birth could make the starting point followed by successive maturation along with increase of individual skills. Further events like foundation of a family, stages of career, coping with dramatic diseases, loss of abilities, and finally the death mark crucial events within a human life cycle. Even beyond biology, life cycles are present in various contexts, for instance when elucidating the quality of durable technical products such as cars. Social scenarios or games with several players incorporate consideration of life cycles as well. Provided by logfiles or monitoring reports, dedicated accumulation of events facilitates identification of life cycles whose statistical analysis promises valuable insights. To this end, we formalise an individual by a set of attributes. Based on its underlying initial assignment ("genetic potential"), events can update corresponding attribute values. Furthermore, events might create new individuals but also kill or merge existing ones. For modelling and evaluation of life cycles, we introduce action-accumulating P systems inspired by dealing with events which in turn result in actions at the system's level. Two case studies demonstrate practical benefits from our approach: We explore the survival of pieces in the board game Mensch argere Dich nicht (Man, don't get annoyed - a variation of Ludo). Secondly, we interpret pseudonymised data from 1,108 students who attended our university course Introduction to Programming stating main factors to improve the final grade with emphasis on the effect of passing a line of exercises and practical training offers.
机译:随着时间的推移,一系列可感知的事件或记录的观察通常在宏观角度下见证了个体的生命周期。如果是人类,出生可以使起点随后是连续成熟以及增加个人技能。进一步的事件,就像一个家庭的基础,职业阶段,应对戏剧性疾病,丧失能力丧失,最后死亡标志在人类生命周期内的重要事件。即使是生物学,甚至在各种情况下都存在生命周期,例如,阐明汽车等耐用技术产品的质量。具有几个玩家的社交场景或游戏也融合了生命周期。由日志文件或监控报告提供,专用事件累积有助于识别统计分析承诺有价值的见解。为此,我们通过一组属性来形式化个人。基于其底层初始分配(“遗传潜力”),事件可以更新相应的属性值。此外,事件可能会创建新的个人,但也会杀死或合并现有的人。对于寿命周期的建模和评估,我们介绍了通过处理事件的动作累积的P系统,这反过来导致系统级别的动作。两种案例研究表明了我们的方法的实际好处:我们探讨了董事会游戏中的碎片的生存,曼彻·赫里德尼希特(男子,不要生气 - 卢迪的变化)。其次,我们从出席大学课程的1,108名学生解释了关于编程的主要因素,以改善最终成绩的主要因素,重点是通过练习和实践培训优惠的效果。

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