The aim of this short note is twofold: recounting how our research group became interested in fuzzy logic, and briefly discussing a definition of fuzzy logic suggested by Bĕhounek and Cintula (see [1]doi:10.1007/978-3-642-35641-4-32Roberto GiuntiniFrancesco PaoliHector FreytesAntonio LeddaGiuseppe SergioliStudies in Fuzziness & S...
Among various combinations of methodologies in soft computing, the one that has highest visibility at this juncture is that of fuzzy logic and neurocomputing, leading to neuro-fuzzy systems. Within fuzzy logic, such systems play a particularly important role in the induction of rules from observatio...
In the partnership of fuzzy logic, neuro- computing, and probabilistic reasoning, fuzzy logic is mainly concerned with imprecision and approximate reason- ing; neurocomputing with learning and curve-fitting; and probabilistic reason- ing with uncertainty and belief propa- gation. We can imagine this...
In large measure, the methodologies are complementary; and yet, there is an element of competition among them. In this setting, what makes sense is formation of a coalition. It is this perception that motivated the genesis of soft computing − a coalition of fuzzy logic, neurocomputing, ...
But if human thought is ultimately fuzzy, how is precise reasoning possible in science and mathematics? Unlike Rosch and Mervis, who searched for a cognitive source of fuzziness, Immanuel Kant (1800) maintained that the open-ended variability of nature is the cause of fuzziness: Since the ...
Unsupervised learning is a machine learning branch for interpreting unlabeled data. Discover how it works and why it is important with videos, tutorials, and examples.
Also, it is important to highlight that this paper focuses on how the decision-mak- ing process is conducted in unstable conditions; in other words, it focuses on how non-binary logic can further support organizations and their resilience in adapting to changing environments and adopting both ...
The next phase is the selection phase where methods are used to evaluate possible alternatives. This phase has two steps: evaluating and making decisions. Many methods can be used in the evaluating steps, such as fuzzy set,cloud computing,granular computingand some visualization tools like Gephi....
There is a significant body of work in explainable AI that focuses on providing users with interpretable outputs that help them improve a system’s performance, and explanations that help users understand why they are getting a specific output. The widening gap between theory and practice in XAI,...
Which is all to say that wherever science malfeasance has been monetised, the people engaged in it would have to be foolish to turn down the moneyteat provided by monetising the citations as well. Who knows what previously-unexplored domains of bogosity await usin the Off-world colonieson the...