Könyv Multi-Valued Logic for Decision-Making Under Uncertainty Evgeny Kagan

Multi-Valued Logic for Decision-Making Under Uncertainty

Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Kiadói készleten rendelésre
Küldés 17-27 napon belül
77 684 Ft
Multi-valued and fuzzy logics provide mathematical and computational tools for handling imperfect in...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2024
oldal
305
EAN
9783031747618
Enbook ID
46539910
Súly
457
Méretek
155 x 235

Teljes leírás

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.

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