Topic
Abductive reasoning
About: Abductive reasoning is a research topic. Over the lifetime, 1917 publications have been published within this topic receiving 44645 citations. The topic is also known as: abduction & abductive inference.
Papers published on a yearly basis
Papers
More filters
01 Jan 2022
10 May 2022
TL;DR: In this article , a modified version of the Echo model, UEcho, is proposed to handle belief acquisition and dynamic belief revision, two essential components of human abductive reasoning, in which a learning mechanism for belief acquisition is added and a dynamic processing mechanism is added for belief revision.
Abstract: This paper explores the uncertainty aspects of human abductive reasoning. Echo, a model of abduction based on the Theory of Explanatory Coherence (Thagard, 1992a), captures many aspects of human abductive reasoning, but fails to sufficiently manage the uncertainty in abduction. In particular, Echo dons not handle belief acquisition and dynamic belief revision, two essential components of human abductive reasoning. We propose a modified Echo model (UEcho), in which we add a learning mechanism for belief acquisition and a dynamic processing mechanism for belief revision. To evaluate the model, we report an empirical study in which base rate learning serves as a testbed for belief acquisition and the order effect serves as a testbed for belief revision.
01 Jan 2019
TL;DR: This chapter first introduces knowledge utilization on pictorial data, and introduces inference, which turns out that conventional deductive inference is in this case of little use.
Abstract: This chapter first introduces knowledge utilization on pictorial data. That is, it introduces inference. It turns out that conventional deductive inference is in this case of little use. Instead abductive inference is used, which brings with it certain risks of failure. The Gestalt-laws proved quite universal and stable inferences from parts to aggregates. They can thus be included in knowledge-based image analysis systems, as kind of default robust constructions. Then only the domain specific knowledge parts must be added. Two examples for such cooperation between perceptual grouping along the laws of Gestalt operations on one side and automatic knowledge utilization on the other hand are given, both on remotely sensed data: 1) Thermal hyper-spectra are analyzed. These are given by an aerial spectrometer on the geographic plane. On this plane Gestalt organization can to a certain degree recognize certain repetitive patterns in a hierarchy, while knowledge about urban objects and their mutual organization, as well as knowledge about spectra of certain materials, can be utilized for classification. 2) The synthetic aperture radar data used as example for lattice grouping