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Abduction aiming at empirical progress or even truth approximation leading to a challenge for computational modelling

机译:旨在经验进步甚至真相逼近的绑架,给计算建模带来挑战

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This paper primarily deals with the conceptual prospects for generalizing the aim of abduction from the standard one of explaining surprising or anomalous observations to that of empirical progress or even truth approximation, It turns out that the main abduction task then becomes the instrumentalist task of theory revision aiming at an empirically more successful theory, relative to the available data, but not necessarily compatible with them. The rest, that is, genuine empirical progress as well as observational, referential and theoretical truth approximation, is a matter of evaluation and selection, and possibly new generation tasks for further improvement, The paper concludes with a survey of possible points of departure, in AI and logic, for computational treatment of the instrumentalist task guided by the 'comparative evaluation matrix'.
机译:本文主要从概括解释绑架目标的概念前景出发,将绑架目标从解释令人惊讶或反常的观察结果的标准之一扩展到经验进展甚至真值逼近的标准,事实证明,主要绑架任务随后成为理论修正的工具主义任务相对于可用数据,但不一定与它们兼容的目标是在经验上更成功的理论。剩下的,即真正的经验进步以及观察,参考和理论真相的逼近,是评估和选择的问题,可能还有进一步改进的新一代任务。本文最后对可能的出发点进行了调查。 AI和逻辑,以“比较评估矩阵”为指导,对工具主义任务进行计算处理。

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