Reasoning Under Uncertainty.

1995 ◽  
Author(s):  
Joseph Y. Halpern
Keyword(s):  
Reasoning Under Uncertainty

Reasoning Under Uncertainty

1990 ◽  
Vol 4 (1) ◽  
pp. 37-72 ◽  
Author(s):  
J Pearl
Keyword(s):  
Reasoning Under Uncertainty

Driver Support Functions Under Resource-Limited Situations

2007 ◽  
Vol 51 (4) ◽  
pp. 176-180 ◽  
Author(s):  
T. Inagaki ◽  
M. Itoh ◽  
Y. Nagai
Keyword(s):  
Situation Awareness ◽  
Driving Simulator ◽  
Reasoning Under Uncertainty ◽  
Support Functions ◽  
Traffic Condition ◽  
Monitoring Method ◽  
Safety Control ◽  
Resource Limited ◽  
Action Type ◽  
Driver Support

What type of support should be given to an automobile driver when it is determined, via some monitoring method, that the driver's situation awareness may not be appropriate to a given traffic condition? With a driving simulator, the following three conditions were compared: (a) Warning type support in which an auditory warning is given to the driver to enhance situation awareness, (b) action type support in which an autonomous safety control action is executed to avoid an accident, and (c) the no-aid baseline condition. Although the both types of driver support are effective, the warning type support sometimes fail to assure safety, which suggests a limitation of the human locus of control assumption. Efficacy of the action type support can also be degraded due to a characteristic of human reasoning under uncertainty. This paper discusses viewpoints needed in the design of systems for supporting drivers in resource-limited situations.

Reasoning Under Uncertainty in Knowledge Graphs

2020 ◽  
pp. 131-139
Author(s):  
Luigi Bellomarini ◽  
Eleonora Laurenza ◽  
Emanuel Sallinger ◽  
Evgeny Sherkhonov
Keyword(s):  
Reasoning Under Uncertainty ◽  
Knowledge Graphs

Default Reasoning for Forensic Visual Surveillance Based on Subjective Logic and its Comparison with L-Fuzzy Set Based Approaches

2013 ◽  
pp. 51-94
Author(s):  
Seunghan Han ◽  
Walter Stechele
Keyword(s):  
Fuzzy Set ◽  
Default Logic ◽  
Visual Surveillance ◽  
Default Reasoning ◽  
Illustrative Case ◽  
Reasoning Under Uncertainty ◽  
Subjective Logic ◽  
Continuous Space ◽  
Uncertainty Handling ◽  
Belief Theory

Default reasoning can provide a means of deriving plausible semantic conclusion under imprecise and contradictory information in forensic visual surveillance. In such reasoning under uncertainty, proper uncertainty handling formalism is required. A discrete species of Bilattice for multivalued default logic demonstrated default reasoning in visual surveillance. In this article, the authors present an approach to default reasoning using subjective logic that acts in a continuous space. As an uncertainty representation and handling formalism, subjective logic bridges Dempster Shafer belief theory and second order Bayesian, thereby making it attractive tool for artificial reasoning. For the verification of the proposed approach, the authors extend the inference scheme on the bilattice for multivalued default logic to L-fuzzy set based logics that can be modeled with continuous species of bilattice structures. The authors present some illustrative case studies in visual surveillance scenarios to contrast the proposed approach with L-fuzzy set based approaches.

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