Introduction -- Elements of Subjective Opinions -- Opinion Representations -- Decision-Making Under Vagueness and Uncertainty -- Principles of Subjective Logic -- Addition, Subtraction and Complement -- Binomial Multiplication and Division -- Multinomial Multiplication and Division -- Conditional Deduction -- Conditional Abduction -- Joint and Marginal Opinions -- Fusion of Subjective Opinions -- Unfusion and Fission of Subjective Opinions -- Computational Trust -- Trust Networks -- Bayesian Reputation Systems -- Subjective Networks.

This is the first comprehensive treatment of subjective logic and all its operations. The author developed the approach, and in this book he first explains subjective opinions, opinion representation, and decision-making under vagueness and uncertainty, and he then offers a full definition of subjective logic, harmonising the key notations and formalisms, concluding with chapters on trust networks and subjective Bayesian networks, which when combined form general subjective networks. The author shows how real-world situations can be realistically modelled with regard to how situations are perceived, with conclusions that more correctly reflect the ignorance and uncertainties that result from partially uncertain input arguments. The book will help researchers and practitioners to advance, improve and apply subjective logic to build powerful artificial reasoning models and tools for solving real-world problems. A good grounding in discrete mathematics is a prerequisite.