scholarly journals A Description Logic for Analogical Reasoning

2021 ◽  
Author(s):  
Steven Schockaert ◽  
Yazmin Ibanez-Garcia ◽  
Victor Gutierrez-Basulto
Keyword(s):  
Analogical Reasoning ◽  
Description Logic ◽  
Alternative Semantics ◽  
Widespread Adoption ◽  
Explainable Ai ◽  
Significant Barrier ◽  
Reasoning By Analogy ◽  
Plausible Inference

Ontologies formalise how the concepts from a given domain are interrelated. Despite their clear potential as a backbone for explainable AI, existing ontologies tend to be highly incomplete, which acts as a significant barrier to their more widespread adoption. To mitigate this issue, we present a mechanism to infer plausible missing knowledge, which relies on reasoning by analogy. To the best of our knowledge, this is the first paper that studies analogical reasoning within the setting of description logic ontologies. After showing that the standard formalisation of analogical proportion has important limitations in this setting, we introduce an alternative semantics based on bijective mappings between sets of features. We then analyse the properties of analogies under the proposed semantics, and show among others how it enables two plausible inference patterns: rule translation and rule extrapolation.

scholarly journals A quantitative, multi-national and multi-stakeholder assessment of barriers to the adoption of cell therapies

2017 ◽  
Vol 8 ◽  
pp. 204173141772441 ◽  
Author(s):  
Benjamin M Davies ◽  
James Smith ◽  
Sarah Rikabi ◽  
Karolina Wartolowska ◽  
Mark Morrey ◽  
...  
Keyword(s):  
Stem Cell ◽  
Cost Effectiveness ◽  
Perceived Barriers ◽  
Healthcare Sector ◽  
Online Questionnaire ◽  
Cell Therapies ◽  
Cellular Therapies ◽  
Widespread Adoption ◽  
Significant Barrier ◽  
Multi Stakeholder

Cellular therapies, such as stem cell–based treatments, have been widely researched and numerous products and treatments have been developed. Despite this, there has been relatively limited use of these technologies in the healthcare sector. This study sought to investigate the perceived barriers to this more widespread adoption. An anonymous online questionnaire was developed, based on the findings of a pilot study. This was distributed to an audience of clinicians, researchers and commercial experts in 13 countries. The results were analysed for all respondents, and also sub-grouped by geographical region, and by profession of respondents. The results of the study showed that the most significant barrier was manufacturing, with other factors such as efficacy, regulation and cost-effectiveness being identified by the different groups. This study further demonstrates the need for these important issues to be addressed during the development of cellular therapies to enable more widespread adoption of these treatments.

Why Precedent in Law (and Elsewhere) is Not Totally (or Even Substantially) About Analogy

2008 ◽  
Vol 3 (6) ◽  
pp. 454-460 ◽  
Author(s):  
Frederick Schauer
Keyword(s):  
Decision Maker ◽  
Analogical Reasoning ◽  
Psychological Literature ◽  
Legal Principle ◽  
Argument By Analogy ◽  
Important Form ◽  
Prior Decision ◽  
Reasoning By Analogy

Cognitive scientists who conduct research on analogical reasoning often claim that precedent in law is an application of reasoning by analogy. In fact, however, law's principle of precedent, as well as the use of precedent in ordinary argument, is quite different. The typical use of analogy in law, including analogies to earlier decisions, involves retrieval of a source analog (or exemplar) from multiple candidates in order to help make the best decision now. But the legal principle of precedent requires that a prior decision be treated as binding even if the current decision maker disagrees with that decision. When the identity between a prior decision and the current question is obvious and inescapable, precedent thus imposes a constraint different from the effect of a typical argument by analogy. The importance of distinguishing analogy from precedent is not so much in showing that a common claim in the psychological literature is mistaken, but that making decisions under the constraints of binding precedent is an important form of decision deserving to be researched in its own right and that it has been ignored because of the erroneous conflation of constraint by precedent with reasoning by analogy.

scholarly journals Loop formulas for description logic programs

2010 ◽  
Vol 10 (4-6) ◽  
pp. 531-545 ◽  
Author(s):  
YISONG WANG ◽  
JIA-HUAI YOU ◽  
LI YAN YUAN ◽  
YI-DONG SHEN
Keyword(s):  
Semantic Web ◽  
Description Logic ◽  
Description Logics ◽  
Answer Set Programming ◽  
Desirable Property ◽  
Logic Programs ◽  
Alternative Semantics ◽  
Answer Set Semantics ◽  
Answer Sets ◽  
Answer Set

AbstractDescription Logic Programs (dl-programs) proposed by Eiter et al. constitute an elegant yet powerful formalism for the integration of answer set programming with description logics, for the Semantic Web. In this paper, we generalize the notions of completion and loop formulas of logic programs to description logic programs and show that the answer sets of a dl-program can be precisely captured by the models of its completion and loop formulas. Furthermore, we propose a new, alternative semantics for dl-programs, called the canonical answer set semantics, which is defined by the models of completion that satisfy what are called canonical loop formulas. A desirable property of canonical answer sets is that they are free of circular justifications. Some properties of canonical answer sets are also explored.

A Method for Reasoning by Analogy in Failure Analysis

1989 ◽  
Vol 111 (3) ◽  
pp. 306-310 ◽  
Author(s):  
J. P. Morrill ◽  
D. Wright
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Hydrogen Embrittlement ◽  
Computer Program ◽  
Error Rate ◽  
Analogical Reasoning ◽  
Current Case ◽  
Modes Of Failure ◽  
Mode Of Failure ◽  
Reasoning By Analogy

An artificial intelligence computer program is being developed for automating the analysis of metallurgical failures. The purpose of this expert system is for recognizing modes of failure like stress corrosion and hydrogen embrittlement. We have previously described a method for recognizing mode of failure based on a form of diagnosis or statistical categorization. In this paper, an alternative method is developed for recognizing mode of failure as a means of confirming or disconfirming the conclusions derived by categorizing. This method is a form of reasoning by analogy that recognizes when the current case is similar to some previously encountered case and uses this information to draw conclusions. The expert system is “programmed” by providing a set of correctly solved examples rather than IF-THEN rules. Accuracy of analogical reasoning is found to increase with number of stored examples, and in recognizing modes of failure an error rate as low as 20.7 percent is observed to occur.

scholarly journals DL-Lite Contraction and Revision

2016 ◽  
Vol 56 ◽  
pp. 329-378 ◽  
Author(s):  
Zhiqiang Zhuang ◽  
Zhe Wang ◽  
Kewen Wang ◽  
Guilin Qi
Keyword(s):  
Finite Number ◽  
Infinite Number ◽  
Description Logic ◽  
Belief Change ◽  
Knowledge Bases ◽  
Theoretic Approach ◽  
Alternative Semantics ◽  
Representation Theorems ◽  
Standard Description ◽  
Model Based

Two essential tasks in managing description logic knowledge bases are eliminating problematic axioms and incorporating newly formed ones. Such elimination and incorporation are formalised as the operations of contraction and revision in belief change. In this paper, we deal with contraction and revision for the DL-Lite family through a model-theoretic approach. Standard description logic semantics yields an infinite number of models for DL-Lite knowledge bases, thus it is difficult to develop algorithms for contraction and revision that involve DL models. The key to our approach is the introduction of an alternative semantics called type semantics which can replace the standard semantics in characterising the standard inference tasks of DL-Lite. Type semantics has several advantages over the standard one. It is more succinct and importantly, with a finite signature, the semantics always yields a finite number of models. We then define model-based contraction and revision functions for DL-Lite knowledge bases under type semantics and provide representation theorems for them. Finally, the finiteness and succinctness of type semantics allow us to develop tractable algorithms for instantiating the functions.

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