Application of fuzzy logic to social choice theory by John N. Mordeson

By John N. Mordeson

Fuzzy social selection concept comes in handy for modeling the uncertainty and imprecision widely used in social lifestyles but it's been scarcely utilized and studied within the social sciences. Filling this hole, Application of Fuzzy good judgment to Social selection Theory presents a accomplished learn of fuzzy social selection theory.

The ebook explains the idea that of a fuzzy maximal subset of a suite of choices, fuzzy selection features, the factorization of a fuzzy choice relation into the "union" (conorm) of a strict fuzzy relation and an indifference operator, fuzzy non-Arrowian effects, fuzzy models of Arrow’s theorem, and Black’s median voter theorem for fuzzy personal tastes. It examines how unambiguous and distinct offerings are generated by means of fuzzy personal tastes and even if certain offerings prompted by way of fuzzy personal tastes fulfill yes believable rationality family. The authors additionally expand recognized Arrowian effects concerning fuzzy set concept to effects concerning intuitionistic fuzzy units in addition to the Gibbard–Satterthwaite theorem to the case of fuzzy susceptible choice family members. the ultimate bankruptcy discusses Georgescu’s measure of similarity of 2 fuzzy selection functions.

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2) Let x, y, z ∈ X be such that ρC (x, y) > 0, ρC (y, z) > 0. By condition α, C(1{x,y,z} ) ∩ 1{x,z} ⊆ C(1{x,z} ). Thus (i) if C(1{x,y,z} )(x) > 0, then C(1{x,z} )(x) > 0 by condition α. (ii) Suppose C(1{x,y,z} )(y) > 0. Then C(1{x,y} )(y) > 0 by condition α. Hence by condition β, C(1{x,y} ) ⊆ C(1{x,y,z} ). Since C(1{x,y} )(x) = ρC (x, y) > 0, C(1{x,y,z} )(x) > 0. Thus by (i), C(1{y,z} )(x) > 0. Suppose C(1{x,y,z} )(z) > 0. Then by condition α, C(1{y,z} )(z) > 0. By condition β, C(1{y,z} ) ⊆ C(1{x,y,z} ) and so C(1{x,y,z} )(y) > 0 since C(1{y,z} )(y) = ρC (y, z) > 0.

The desired result now follows since ρC (x, w) = tx,w if ρ(w, x) > ρ(x, w) and ρ(x, w) > ρ(w, x) ⇔ ρC (x, w) > ρC (w, x). 6 Let C be a fuzzy choice function on X and let ρ ∈ FR(X). Suppose ρ rationalizes C. Then ∀x ∈ X, ρC (x, x) = 1. Recall that in the crisp case, condition α requires that if an alternative x is chosen from a set T and S is a subset of T containing x, then x should still be chosen. 7 Let C be a fuzzy choice function on X. Then C is said to satisfy condition α if ∀µ, ν ∈ FP ∗ (X), µ ⊆ ν implies C(ν) ∩ µ ⊆ C(µ).

Then C is said to be full rational if C = G( , ρ) for some reflexive, max-∗ transitive, and strongly total fuzzy preference relation ρ. 22 Let C be a fuzzy choice function on a fuzzy choice space (X, B). Then C is said to satisfy the fuzzy Arrow axiom FAA if for all µ1 , µ2 ∈ B and for all x ∈ X, I(µ1 , µ2 ) ∗ µ1 (x) ∗ C(µ2 )(x) ≤ E(µ1 ∩ C(µ2 ), C(µ1 )). 23 (Georgescu [24]) If C : B → FP(X) is a fuzzy choice function, then the following statements are equivalent: (1) C is full rational; (2) C satisfies F AA.

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