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.
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01 Jan 2022
01 Jan 2022
TL;DR: In this article , a more flexible, adaptable, and rigorous approach to the generation of both descriptive and explanatory new knowledge is offered, translating different types of reasoning into a set of logics of inquiry.
Abstract: As a counter to the dominant tradition in management research, where the measurement and classification of a few variables is used to refine and test existing theory, to the neglect of theory generation, a more flexible, adaptable, and rigorous approach to the generation of both descriptive and explanatory new knowledge is offered. This scheme translates different types of reasoning into a set of logics of inquiry – inductive, deductive, abductive, and retroductive. Each logic has a characteristic starting point, steps, and end point, and is used within particular ontological assumptions. Consideration is also given to dealing with inconsistencies and contradictions between statements in bodies of knowledge. Traditional (pattern-context) driven and combinatorial (data-pattern) driven approaches to social inquiry are compared and these make possible the braiding of small-data and big-data.KeywordsAbductionContradictionDeductionInductionLogicOntologyParadigmResearch questionRetroduction
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TL;DR: The authors reformulate abduction as a social process, occurring not only within individual scientists but often through conversation between those who understand a particular scientific system and its anomalies (its insiders) and those exposed to alien and disruptive patterns, theories, and findings that could resolve them (its outsiders).
Abstract: The logic of abduction involves a collision between deduction and induction, where empirical surprises violate expectations and scientists innovate to resolve them. Here we reformulate abduction as a social process, occurring not only within individual scientists, but often through conversation between those who understand a particular scientific system and its anomalies (its insiders) and those exposed to alien and disruptive patterns, theories, and findings that could resolve them (its outsiders). These extended conversations between scientists, scholars, and disciplines with divergent backgrounds define a social logic of discovery by catalyzing social syllogisms that yield speculative hypotheses with outsized impact across science. We show how this approach theorizes a number of disparate findings from scientometrics and the science and science, tethering them to powerful interpersonal processes that link diversity with discovery. By reframing abductive reasoning as a social process, we attempt to broker a productive new relationship between science studies' focus on scientific practice and the philosophy of science's concern with propositions in scientific discourse, rendering claims-making through abduction a critical scientific practice, central to scientific change, and increasingly available to science studies through small and large-scale data on scientific communication and deliberation.
27 Sep 2015
TL;DR: My work on PhD thesis consists in nonmonotonic reasoning about spatial relations and how they change in time and introducing the so-called ASPMT(QS) system, based on a paradigm of Answer Set Programming Modulo Theories and polynomial encodings of spatial relations.
Abstract: My work on PhD thesis consists in nonmonotonic reasoning about spatial relations and how they change in time. Although there are several approaches concerning this topic, to the best of my knowledge, there is no general framework that provides nonmonotonic (qualitative) spatial reasoning. The work I have accomplished so far consists in introducing the so-called ASPMT(QS) system. It is based on a paradigm of Answer Set Programming Modulo Theories (ASPMT) and polynomial encodings of spatial relations. The system enables modelling of dynamically varying spatial information, as well as abductive reasoning, and its first version is already implemented. As a future work I consider extending ASPMT(QS) in order to perform more complex spatio-temporal reasoning and try to overcome limitations of the current implementation.
29 Aug 2012
TL;DR: A novel approach for high-level action recognition in surveillance videos combining Linear Temporal Logic (LTL) and Abductive Reasoning is proposed by first mapping the surveillance videos to LTL formula and then using probabilistic and logical reasoning to identify complex events like burglary/escapade or deal with arbitrary events like occlusion or random stops.
Abstract: : Real time motion tracking is a very important part of activity recognition from streaming videos. But little research has been done in recognizing the top-level plans linking the atomic activities evident in various surveillance footages. This paper proposes a novel approach for high-level action recognition in surveillance videos combining Linear Temporal Logic (LTL) and Abductive Reasoning. Although both LTL and Abductive reasoning have been used separately for plan recognition in various Artificial Intelligence (AI) systems and mobile robots, the framework proposed in this paper combines the two by first mapping the surveillance videos to LTL formula and then using probabilistic and logical reasoning to identify complex events like burglary/escapade or deal with arbitrary events like occlusion or random stops.