Multi-Valued Logic for Decision-Making Under Uncertainty

By Ronald Yager, Evgeny Kagan, Alexander Rybalov

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.

• Format: Hardcover
• Language: English
• ISBN: 3031747615
• ISBN13: 9783031747618
• Release Date: February 2025
• Publisher: Birkhauser
• Length: 194 Pages
• Weight: 1.05 lbs.
• Dimensions: 0.6" x 6.4" x 9.5"