Qualitative Spatial Reasoning

2011 ◽  
pp. 3175-3180
Author(s):  
Shyamanta M. Hazarika
Keyword(s):  
Common Sense ◽  
Spatial Reasoning ◽  
Qualitative Reasoning ◽  
Physical Situation ◽  
Qualitative Spatial Reasoning ◽  
Common Sense Reasoning ◽  
Naive Physics ◽  
Qualitative Physics ◽  
And Mathematics ◽  
Common Sense Knowledge

Artificial Intelligence (AI) has, as one of its central topics, the ability to represent and reason with common sense knowledge. Early forays into common sense reasoning about the physical world involved solving textbook problems on physics and mathematics. These were not adequate for reasoning about most commonplace physical scenarios. A system suggested by DeKleer, involving both quantitative knowledge and qualitative information concerning the physical situation marked the starting point for qualitative physics (Weld & DeKleer, 1990). Hayes’ Naive Physics Manifesto (Hayes, 1985) paved the way for establishing qualitative physics (meantime re-christened qualitative reasoning) as an important topic of research within AI. Qualitative Reasoning (QR) is an approach for dealing with common sense knowledge without recourse to complete quantitative knowledge. Representation of knowledge is through a limited repository of qualitative abstractions. Space and spatial change is an important part of common sense reasoning. Naive Physics Manifesto proposed to represent space-time with four-dimensional histories. Despite early forays such as the Naive Physics Manifesto, representation of space within QR has been ill addressed. Nevertheless, there has been an increasing interest over the last few years in qualitative spatial reasoning - reasoning about space using qualitative abstractions.

scholarly journals FULL-FLEDGED SEMANTIC ANALYSIS AS A TOOL FOR RESOLVING TRIANGLE-COPA SOCIAL SCENARIOS

2020 ◽  
Author(s):  
I. M. Boguslavsky ◽  
◽  
V. G. Dikonov ◽  
T. I. Frolova ◽  
L. L. Iomdin ◽  
...  
Keyword(s):  
Common Sense ◽  
Semantic Analysis ◽  
Multiple Choice ◽  
General Purpose ◽  
Published Data ◽  
Data Set ◽  
Text Interpretation ◽  
Common Sense Reasoning ◽  
Two Alternatives ◽  
Common Sense Knowledge

Text interpretation often requires common sense knowledge and reasoning. A convenient tool for developing methods of common sense reasoning are special sets of challenge problems whose interpretation requires sophisticated reasoning. An interesting example is a recently published data set called Triangle Choice of Plausible Alternatives (Triangle-COPA), which contains 100 multiple-choice problems that test the interpretation of social scenarios. Each problem includes a statement and two alternatives. The task is to identify the more plausible alternative. For processing Triangle-COPA data we use SemETAP, a general purpose semantic analyzer. We implement the full scenario of NL understanding starting from NL texts and not from manually composed simplified logical formulas, which is a common practice in logic-based approaches to common sense reasoning. We produce Enhanced Semantic Structures of the statement and both alternatives and check which alternative manifests more semantic agreement with the statement in terms of inferences.

scholarly journals Arithmetic Word Problems Revisited: Cognitive Processes and Academic Performance in Secondary School

2021 ◽  
Vol 11 (4) ◽  
pp. 155
Author(s):  
Gonzalo Duque de Blas ◽  
Isabel Gómez-Veiga ◽  
Juan A. García-Madruga
Keyword(s):  
Academic Performance ◽  
Word Problems ◽  
Spatial Reasoning ◽  
Deductive Reasoning ◽  
Executive Processes ◽  
Mathematical Operation ◽  
Visual Spatial ◽  
And Mathematics ◽  
The One ◽  
Memory Resources

Solving arithmetic word problems is a complex task that requires individuals to activate their working memory resources, as well as the correct performance of the underlying executive processes involved in order to inhibit semantic biases or superficial responses caused by the problem’s statement. This paper describes a study carried out with 135 students of Secondary Obligatory Education, each of whom solved 5 verbal arithmetic problems: 2 consistent problems, whose mathematical operation (add/subtract) and the verbal statement of the problem coincide, and 3 inconsistent problems, whose required operation is the inverse of the one suggested by the verbal term(s). Measures of reading comprehension, visual–spatial reasoning and deductive reasoning were also obtained. The results show the relationship between arithmetic problems and cognitive measures, as well as the ability of these problems to predict academic performance. Regression analyses confirmed that arithmetic word problems were the only measure with significant power of association with academic achievement in both History/Geography (β = 0.25) and Mathematics (β = 0.23).

scholarly journals The liberation of nature and knowledge: a case study on Hans Reichenbach’s naturalism

Synthese ◽  
2021 ◽  
Author(s):  
László Kocsis ◽  
Adam Tamas Tuboly
Keyword(s):  
Common Sense ◽  
Interesting Case ◽  
Valuable Contribution ◽  
Rhetorical Strategy ◽  
Scientific Philosophy ◽  
Political Program ◽  
History Of ◽  
Contemporary Context ◽  
Common Sense Knowledge

AbstractOur main goal in this paper is to present and scrutinize Reichenbach’s own naturalism in our contemporary context, with special attention to competing versions of the concept. By exploring the idea of Reichenbach’s naturalism, we will argue that he defended a liberating, therapeutic form of naturalism, meaning that he took scientific philosophy (or philosophy of nature, Naturphilosophie) to be a possible cure for bad old habits and traditional ways of philosophy. For Reichenbach, naturalistic scientific philosophy was a well-established form of liberation. We do not intend to suggest that Reichenbach acted as an inventor of naturalism; nonetheless, invoking the term and the idea of ‘naturalism’ is more than a simple rhetorical strategy for rehabilitating Reichenbach as a forerunner of this field. We think that his ideas can make a valuable contribution to contemporary debates, and that he presents an interesting case among the other scientifically oriented proponents of his time. After presenting a short reconstruction of the meaning of naturalism—or, more appropriately, naturalisms—in order to be able to correctly situate Reichenbach within his own as well as a systematic context, we discuss Reichenbach’s naturalism against the background of his scientific philosophy, his views on the relation of common-sense knowledge to science, and his efforts at popularization. To delve deeper into this topic, we present a case study to show how Reichenbach argued that in both scientific and philosophical discussions (assuming their naturalistic continuity), it is necessary to move from the request and value of truth to probability. And, finally, we argue that the liberation of knowledge and nature was a socio-political program for Reichenbach, who talked about his own scientific philosophy as “a crusade.” By emphasizing this aspect of Reichenbach’s naturalism, we may be in a better position to situate him in the history of analytic philosophy in general, and in the yet-to-be-written narrative of the naturalistic movement in particular.

A Framework for Building Behavioral Models for Design-Stage Failure Identification Using Dimensional Analysis

2010 ◽  
Author(s):  
Eric Coatane´a ◽  
Tuomas Ritola ◽  
Irem Y. Tumer ◽  
David Jensen
Keyword(s):  
Dimensional Analysis ◽  
Behavioral Model ◽  
Qualitative Reasoning ◽  
Design Stage ◽  
Critical Event ◽  
Behavioral Models ◽  
New Approach ◽  
Design Variables ◽  
Qualitative Physics ◽  
Failure Identification

In this paper, a design-stage failure identification framework is proposed using a modeling and simulation approach based on Dimensional Analysis and qualitative physics. The proposed framework is intended to provide a new approach to model the behavior in the Functional-Failure Identification and Propagation (FFIP) framework, which estimates potential faults and their propagation paths under critical event scenarios. The initial FFIP framework is based on combining hierarchical system models of functionality and configuration, with behavioral simulation and qualitative reasoning. This paper proposes to develop a behavioral model derived from information available at the configuration level. Specifically, the new behavioral model uses design variables, which are associated with units and quantities (i.e., Mass, Length, Time, etc…). The proposed framework continues the work to allow the analysis of functional failures and fault propagation at a highly abstract system concept level before any potentially high-cost design commitments are made. The main contribution in this paper consists of developing component behavioral models based on the combination of fundamental design variables used to describe components and their units or quantities, more precisely describing components’ behavior.

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