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Multi-Valued Logic for Decision-Making Under Uncertainty (Computer Science Foundations and Applied Logic) by Evgeny Kagan, Alexander Rybalov, Ronald Yager is a nonfiction available to read on EtoBox.

What is Multi-Valued Logic for Decision-Making Under Uncertainty (Computer Science Foundations and Applied Logic) about?

Multi-valued and fuzzy logics provide mathematical and computational tools for handling imperfect information and decision-making with rational collective reasoning and irrational individual judgements.The suggested implementation of multi-valued logics is based on the uninorm and absorbing norm with generating functions defined by probability distributions. Natural extensions of these logics result in non-commutative and non-distributive logics. In addition to Boolean truth values, these logics handle subjective truth and false values and model irrational decisions. Dynamics of decision-making are specified by the subjective Markov process and learning – by neural network with extended Tsetlin neurons. Application of the suggested methods is illustrated by modelling of irrational economic decisions and biased reasoning in the wisdom-of-the-crowd method, and by control of mobile robots and navigation of their groups.Topics and featuresBridges the gap between fuzzy and probability methodsIncludes examples in the field of machine-learning and robots’ controlDefines formal models of subjective judgements and decision-makingPresents practical techniques for solving non-probabilistic de

Who reads Multi-Valued Logic for Decision-Making Under Uncertainty (Computer Science Foundations and Applied Logic)?

Author

Evgeny Kagan, Alexander Rybalov, Ronald Yager

Publisher

Springer Basel AG

Published

2025

Language

EN

ISBN

9783031747618

Category

nonfiction

Subjects

Mathematics, Computer Science, Stem