Fr. 237.00

Multi-valued Logic for Decision-Making Under Uncertainty

English · Hardback

Shipping usually within 6 to 7 weeks

Description

Read more

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.

List of contents

1. Introduction.- 2. Background.- 3. Probability-generated multi-valued logic.- 4. Muli-valued logic algebra of subjective trusts.- 5. Algebra with non-commutative norms.- 6. Implementation of subjective trusts in control.

About the author

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.

Product details

Authors Evgeny Kagan, Alexander Rybalov, Ronald Yager
Publisher Springer, Berlin
 
Languages English
Product format Hardback
Released 16.12.2024
 
EAN 9783031747618
ISBN 978-3-0-3174761-8
No. of pages 194
Dimensions 155 mm x 13 mm x 235 mm
Weight 457 g
Illustrations VIII, 194 p. 61 illus., 1 illus. in color.
Series Computer Science Foundations and Applied Logic
Subjects Natural sciences, medicine, IT, technology > IT, data processing > IT

Wahrscheinlichkeitsrechnung und Statistik, Mathematik: Logik, fuzzy logic, Mathematik für Informatiker, Probability and Statistics in Computer Science, Computer Science Logic and Foundations of Programming, Algebraic Logic, Subjective Trusts, Non-commutative Logic, Probability-generated Norms, Multi-valued Logic

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.