Téléchargez le livre : Multi-valued Logic for Decision-Making Under Uncertainty

Multi-valued Logic for Decision-Making Under Uncertainty

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Éditeur :

Birkhäuser

Paru le : 2025-02-17

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 ...
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Description du livre


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 features: Bridges the gap between fuzzy and probability methods Includes examples in the field of machine-learning and robots’ control Defines formal models of subjective judgements and decision-making Presents practical techniques for solving non-probabilistic decision-making problems Initiates further research in non-commutative and non-distributive logics
The book forms a basis for theoretical studies and practice of decision-making under uncertainty and will be useful for computer scientists and mathematicians interested in multi-valued and fuzzy logic, as well as for engineers working in the field of data mining and data analysis.

À propos

Auteur
Evgeny Kagan , Alexander Rybalov , Ronald Yager
Éditeur
Birkhäuser
Collection
n.c
Parution
2025-02-17
Pages
194 pages
EAN papier
9783031747618
Dr. Evgeny Kagan is with the Faculty of Engineering, Ariel University, Israel. Dr. Alexander Rybalov is with the LAMBDA Laboratory, Tel-Aviv University, Israel. Prof. Ronald Yager is with the Machine Learning Institute, Yona College, New York, USA.

Caractéristiques détaillées - droits

EAN PDF
9783031747625
Prix
200,44 €
Nombre pages copiables
1
Nombre pages imprimables
19
Taille du fichier
9308 Ko
Ce livre est accessible aux handicaps informations d'accessibilité
EAN EPUB
9783031747625
Prix
200,44 €
Nombre pages copiables
1
Nombre pages imprimables
19
Taille du fichier
18964 Ko
Ce livre est accessible aux handicaps informations d'accessibilité

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