Construction of t-norms

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In mathematics, t-norms are a special kind of binary operations on the real unit interval [0, 1]. Various constructions of t-norms, either by explicit definition or by transformation from previously known functions, provide a plenitude of examples and classes of t-norms. This is important, e.g., for finding counter-examples or supplying t-norms with particular properties for use in engineering applications of fuzzy logic. The main ways of construction of t-norms include using generators, defining parametric classes of t-norms, rotations, or ordinal sums of t-norms.

Relevant background can be found in the article on t-norms.

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[edit] Generators of t-norms

The method of constructing t-norms by generators consists in using a unary function (generator) to transform some known binary function (most often, addition or multiplication) into a t-norm.

In order to allow using non-bijective generators, which do not have the inverse function, the following notion of pseudo-inverse function is employed:

Let f: [ab] → [cd] be a monotone function between two closed subintervals of extended real line. The pseudo-inverse function to f is the function f (−1): [cd] → [ab] defined as
f^{(-1)}(y) = \begin{cases}
  \sup \{ x\in[a,b] \mid f(x) < y \} & \mbox{for } f \mbox{ non-decreasing} \\
  \sup \{ x\in[a,b] \mid f(x) > y \} & \mbox{for } f \mbox{ non-increasing.}
\end{cases}

[edit] Additive generators

The construction of t-norms by additive generators is based on the following theorem:

Let f: [0, 1] → [0, +∞] be a strictly decreasing function such that f(1) = 0 and f(x) + f(y) is in the range of f or equal to f(0+) or +∞ for all x, y in [0, 1]. Then the function T: [0, 1]2 → [0, 1] defined as
T(x, y) = f (-1)(f(x) + f(y))
is a t-norm.

If a t-norm T results from the latter construction by a function f which is right-continuous in 0, then f is called an additive generator of T.

Examples:

  • The function f(x) = 1 – x for x in [0, 1] is an additive generator of the Łukasiewicz t-norm.
  • The function f defined as f(x) = –log(x) if 0 < x ≤ 1 and f(0) = +∞ is an additive generator of the product t-norm.
  • The function f defined as f(x) = 2 – x if 0 ≤ x < 1 and f(1) = 0 is an additive generator of the drastic t-norm.

Basic properties of additive generators are summarized by the following theorem:

Let f: [0, 1] → [0, +∞] be an additive generator of a t-norm T. Then:
  • T is an Archimedean t-norm.
  • T is continuous if and only if f is continuous.
  • T is strictly monotone if and only if f(0) = +∞.
  • Each element of (0, 1) is a nilpotent element of T if and only if f(0) < +∞.
  • The multiple of f by a positive constant is also an additive generator of T.
  • T has no non-trivial idempotents. (Consequently, e.g., the minimum t-norm has no additive generator.)

[edit] Multiplicative generators

The isomorphism between addition on [0, +∞] and multiplication on [0, 1] by the logarithm and the exponential function allow two-way transformations between additive and multiplicative generators of a t-norm. If f is an additive generator of a t-norm T, then the function g: [0, 1] → [0, 1] defined as g(x) = ef (x) is a multiplicative generator of T, that is, a function h such that

  • h is strictly increasing
  • h(1) = 1
  • h(x) · h(y) is in the range of h or equal to 0 or h(0+) for all x, y in [0, 1]
  • h is right-continuous in 0
  • T(x, y) = h (−1)(h(x) · h(y)).

Vice versa, if g is a multiplicative generator of T, then f: [0, 1] → [0, +∞] defined by f(x) = −log(g(x)) is an additive generator of T.

[edit] Parametric classes of t-norms

Many families of related t-norms can be defined by an explicit formula depending on a parameter p. This section lists the best known parameterized families of t-norms. The following definitions will be used in the list:

  • A family of t-norms Tp parameterized by p is increasing if TpTq for all x, y in [0, 1] whenever pq (similarly for decreasing and strictly increasing or decreasing).
  • A family of t-norms Tp is continuous with respect to the parameter p if
\lim_{p\to p_0} T_p = T_{p_0}
for all values p0 of the parameter.

[edit] Schweizer–Sklar t-norms

Graph (3D and contours) of the Schweizer–Sklar t-norm with p = 2
Graph (3D and contours) of the Schweizer–Sklar t-norm with p = 2

The family of Schweizer–Sklar t-norms, introduced by Berthold Schweizer and Abe Sklar in the early 1960s, is given by the parametric definition

T^{\mathrm{SS}}_p(x,y) = \begin{cases}
  T_{\mathrm{min}}(x,y)          & \mbox{if } p = -\infty \\
  (x^p + y^p - 1)^{1/p}          & \mbox{if } -\infty < p < 0 \\
  T_{\mathrm{prod}}(x,y)         & \mbox{if } p = 0 \\
  (\max(0, x^p + y^p - 1))^{1/p} & \mbox{if } 0 < p < +\infty \\
  T_{\mathrm{D}}(x,y)            & \mbox{if } p = +\infty.
\end{cases}

A Schweizer–Sklar t-norm T^{\mathrm{SS}}_p is

  • Archimedean if and only if p > −∞
  • Continuous if and only if p < +∞
  • Strict if and only if −∞ < p ≤ 0 (for p = −1 it is the Hamacher product)
  • Nilpotent if and only if 0 < p < +∞ (for p = 1 it is the Łukasiewicz t-norm).

The family is strictly decreasing for p ≥ 0 and continuous with respect to p in [−∞, +∞]. An additive generator for T^{\mathrm{SS}}_p for −∞ < p < +∞ is

f^{\mathrm{SS}}_p (x,y) = \begin{cases}
  -\log x           & \mbox{if } p = 0 \\
  \frac{1 - x^p}{p} & \mbox{otherwise.}
\end{cases}

[edit] Hamacher t-norms

The family of Hamacher t-norms, introduced by Horst Hamacher in the late 1970s, is given by the following parametric definition for 0 ≤ p ≤ +∞:

T^{\mathrm{H}}_p (x,y) = \begin{cases}
  T_{\mathrm{D}}(x,y)                & \mbox{if } p = +\infty \\
  0                                  & \mbox{if } p = x = y = 0 \\
  \frac{xy}{p + (1 - p)(x + y - xy)} & \mbox{otherwise.}
\end{cases}

The t-norm T^{\mathrm{H}}_0 is called the Hamacher product.

Hamacher t-norms are the only t-norms which are rational functions. The Hamacher t-norm T^{\mathrm{H}}_p is strict if and only if p < +∞ (for p = 1 it is the product t-norm). The family is strictly decreasing and continuous with respect to p. An additive generator of T^{\mathrm{H}}_p for p < +∞ is

f^{\mathrm{H}}_p(x) = \begin{cases}
  \frac{1 - x}{x}            & \mbox{if } p = 0 \\
  \log\frac{p + (1 - p)x}{x} & \mbox{otherwise.}
\end{cases}

[edit] Frank t-norms

The family of Frank t-norms, introduced by M.J. Frank in the late 1970s, is given by the parametric definition for 0 ≤ p ≤ +∞ as follows:

T^{\mathrm{F}}_p(x,y) = \begin{cases}
  T_{\mathrm{min}}(x,y)  & \mbox{if } p = 0 \\
  T_{\mathrm{prod}}(x,y) & \mbox{if } p = 1 \\
  T_{\mathrm{Luk}}(x,y)  & \mbox{if } p = +\infty \\
  \log_p\left(1 + \frac{(p^x - 1)(p^y - 1)}{p - 1}\right) & \mbox{otherwise.}
\end{cases}

The Frank t-norm T^{\mathrm{F}}_p is strict if p < +∞. The family is strictly decreasing and continuous with respect to p. An additive generator for T^{\mathrm{F}}_p is

f^{\mathrm{F}}_p(x,y) = \begin{cases}
  -\log x                   & \mbox{if } p = 1 \\
  1 - x                     & \mbox{if } p = +\infty \\
  \log\frac{p - 1}{p^x - 1} & \mbox{otherwise.}
\end{cases}

[edit] Yager t-norms

Graph of the Yager t-norm with p = 2
Graph of the Yager t-norm with p = 2

The family of Yager t-norms, introduced in the early 1980s by Ronald R. Yager, is given for 0 ≤ p ≤ +∞ by

T^{\mathrm{Y}}_p (x,y) = \begin{cases}
  T_{\mathrm{D}}(x,y)   & \mbox{if } p = 0 \\
  \max\left(0, 1 - ((1 - x)^p + (1 - y)^p)^{1/p}\right) & \mbox{if } 0 < p < +\infty \\
  T_{\mathrm{min}}(x,y) & \mbox{if } p = +\infty
\end{cases}

The Yager t-norm T^{\mathrm{Y}}_p is nilpotent if and only if 0 < p < +∞ (for p = 1 it is the Łukasiewicz t-norm). The family is strictly increasing and continuous with respect to p. The Yager t-norm T^{\mathrm{Y}}_p for 0 < p < +∞ arises from the Łukasiewicz t-norm by raising its additive generator to the power of p. An additive generator of T^{\mathrm{Y}}_p for 0 < p < +∞ is

f^{\mathrm{Y}}_p(x) = (1 - x)^p.

[edit] Aczél–Alsina t-norms

The family of Aczél–Alsina t-norms, introduced in the early 1980s by János Aczél and Claudi Alsina, is given for 0 ≤ p ≤ +∞ by

T^{\mathrm{AA}}_p (x,y) = \begin{cases}
  T_{\mathrm{D}}(x,y)   & \mbox{if } p = 0 \\
  e^{-\left(|\log x|^p + |\log y|^p\right)^{1/p}} & \mbox{if } 0 < p < +\infty \\
  T_{\mathrm{min}}(x,y) & \mbox{if } p = +\infty
\end{cases}

The Aczél–Alsina t-norm T^{\mathrm{AA}}_p is strict if and only if 0 < p < +∞ (for p = 1 it is the product t-norm). The family is strictly increasing and continuous with respect to p. The Aczél–Alsina t-norm T^{\mathrm{AA}}_p for 0 < p < +∞ arises from the product t-norm by raising its additive generator to the power of p. An additive generator of T^{\mathrm{AA}}_p for 0 < p < +∞ is

f^{\mathrm{AA}}_p(x) = (-\log x)^p.

[edit] Dombi t-norms

The family of Dombi t-norms, introduced by József Dombi (1982), is given for 0 ≤ p ≤ +∞ by

T^{\mathrm{D}}_p (x,y) = \begin{cases}
  0                     & \mbox{if } x = 0 \mbox{ or } y = 0 \\
  T_{\mathrm{D}}(x,y)   & \mbox{if } p = 0 \\
  T_{\mathrm{min}}(x,y) & \mbox{if } p = +\infty \\
  \frac{1}{1 + \left(
    \left(\frac{1 - x}{x}\right)^p + \left(\frac{1 - y}{y}\right)^p
  \right)^{1/p}} & \mbox{otherwise.} \\
\end{cases}

The Dombi t-norm T^{\mathrm{D}}_p is strict if and only if 0 < p < +∞ (for p = 1 it is the Hamacher product). The family is strictly increasing and continuous with respect to p. The Dombi t-norm T^{\mathrm{D}}_p for 0 < p < +∞ arises from the Hamacher product t-norm by raising its additive generator to the power of p. An additive generator of T^{\mathrm{D}}_p for 0 < p < +∞ is

f^{\mathrm{D}}_p(x) = \left(\frac{1-x}{x}\right)^p.

[edit] Sugeno–Weber t-norms

The family of Sugeno–Weber t-norms was introduced in the early 1980s by Siegfried Weber; the dual t-conorms were defined already in the early 1970s by Michio Sugeno. It is given for −1 ≤ p ≤ +∞ by

T^{\mathrm{SW}}_p (x,y) = \begin{cases}
  T_{\mathrm{D}}(x,y)    & \mbox{if } p = -1 \\
  \max\left(0, \frac{x + y - 1 + pxy}{1 + p}\right) & \mbox{if } -1 < p < +\infty \\
  T_{\mathrm{prod}}(x,y) & \mbox{if } p = +\infty 
\end{cases}

The Sugeno–Weber t-norm T^{\mathrm{SW}}_p is nilpotent if and only if −1 < p < +∞ (for p = 0 it is the Łukasiewicz t-norm). The family is strictly increasing and continuous with respect to p. An additive generator of T^{\mathrm{SW}}_p for 0 < p < +∞ [sic] is

f^{\mathrm{SW}}_p(x) = \begin{cases}
  1 - x   & \mbox{if } p = 0 \\
  1 - \log_{1 + p}(1 + px) & \mbox{otherwise.}
\end{cases}

[edit] Ordinal sums

The ordinal sum constructs a t-norm from a family of t-norms, by shrinking them into disjoint subintervals of the interval [0, 1] and completing the t-norm by using the minimum on the rest of the unit square. It is based on the following theorem:

Let Ti for i in an index set I be a family of t-norms and (aibi) a family of pairwise disjoint (non-empty) open subintervals of [0, 1]. Then the function T: [0, 1]2 → [0, 1] defined as
T(x, y) = \begin{cases}
  a_i + (b_i - a_i) \cdot T_i\left(\frac{x - a_i}{b_i - a_i}, \frac{y - a_i}{b_i - a_i}\right)
    & \mbox{if } x, y \in [a_i, b_i]^2 \\
  \min(x, y) & \mbox{otherwise}
\end{cases}
is a t-norm.
Ordinal sum of the Łukasiewicz t-norm on the interval [0.05, 0.45] and the product t-norm on the interval [0.55, 0.95]
Ordinal sum of the Łukasiewicz t-norm on the interval [0.05, 0.45] and the product t-norm on the interval [0.55, 0.95]

The resulting t-norm is called the ordinal sum of the summands (Ti, ai, bi) for i in I, denoted by

T = \bigoplus\nolimits_{i\in I} (T_i, a_i, b_i),

or (T_1, a_1, b_1) \oplus \dots \oplus (T_n, a_n, b_n) if I is finite.

Ordinal sums of t-norms enjoy the following properties:

  • Each t-norm is a trivial ordinal sum of itself on the whole interval [0, 1].
  • The empty ordinal sum (for the empty index set) yields the minimum t-norm Tmin. Summands with the minimum t-norm can arbitrarily be added or omitted without changing the resulting t-norm.
  • It can be assumed without loss of generality that the index set is countable, since the real line can only contain at most countably many disjoint subintervals.
  • An ordinal sum of t-norm is continuous if and only if each summand is a continuous t-norm. (Analogously for left-continuity.)
  • An ordinal sum is Archimedean if and only if it is a trivial sum of one Archimedean t-norm on the whole unit interval.
  • An ordinal sum has zero divisors if and only if for some index i, ai = 0 and Ti has zero divisors. (Analogously for nilpotent elements.)

If T = \bigoplus\nolimits_{i\in I} (T_i, a_i, b_i) is a left-continuous t-norm, then its residuum R is given as follows:

R(x, y) = \begin{cases}
  1 & \mbox{if } x \le y \\
  a_i + (b_i - a_i) \cdot R_i\left(\frac{x - a_i}{b_i - a_i}, \frac{y - a_i}{b_i - a_i}\right)
    & \mbox{if } a_i < y < x \le b_i \\
  y & \mbox{otherwise.}
\end{cases}

where Ri is the residuum of Ti, for each i in I.

[edit] Ordinal sums of continuous t-norms

The ordinal sum of a family of continuous t-norms is a continuous t-norm. By the Mostert–Shields theorem, every continuous t-norm is expressible as the ordinal sum of Archimedean continuous t-norms. Since the latter are either nilpotent (and then isomorphic to the Łukasiewicz t-norm) or strict (then isomorphic to the product t-norm), each continuous t-norm is isomorphic to the ordinal sum of Łukasiewicz and product t-norms.

Important examples of ordinal sums of continuous t-norms are the following ones:

  • Dubois–Prade t-norms, introduced by Didier Dubois and Henri Prade in the early 1980s, are the ordinal sums of the product t-norm on [0, p] for a parameter p in [0, 1] and the (default) minimum t-norm on the rest of the unit interval. The family of Dubois–Prade t-norms is decreasing and continuous with respect to p..
  • Mayor–Torrens t-norms, introduced by Gaspar Mayor and Joan Torrens in the early 1990s, are the ordinal sums of the Łukasiewicz t-norm on [0, p] for a parameter p in [0, 1] and the (default) minimum t-norm on the rest of the unit interval. The family of Mayor–Torrens t-norms is decreasing and continuous with respect to p..

[edit] Rotations

The construction of t-norms by rotation was introduced by Sándor Jenei (2000). It is based on the following theorem:

Let T be a left-continuous t-norm without zero divisors, N: [0, 1] → [0, 1] the function that assigns 1 − x to x and t = 0.5. Let T1 be the linear transformation of T into [t, 1] and R_{T_1}(x,y) = \sup\{z \mid T_1(z,x)\le y\}. Then the function
T_{\mathrm{rot}} = \begin{cases}
  T_1(x, y) & \mbox{if } x, y \in (t, 1] \\
  N(R_{T_1}(x, N(y))) & \mbox{if } x \in (t, 1] \mbox{ and } y \in [0, t] \\
  N(R_{T_1}(y, N(x))) & \mbox{if } x \in [0, t] \mbox{ and } y \in (t, 1] \\
  0 & \mbox{if } x, y \in [0, t]
\end{cases}
is a left-continuous t-norm, called the rotation of the t-norm T.
The nilpotent minimum as a rotation of the minimum t-norm
The nilpotent minimum as a rotation of the minimum t-norm

Geometrically, the construction can be described as first shrinking the t-norm T to the interval [0.5, 1] and then rotating it by the angle 2π/3 in both directions around the line connecting the points (0, 0, 1) and (1, 1, 0).

The theorem can be generalized by taking for N any strong negation, that is, an involutive strictly decreasing continuous function on [0, 1], and for t taking the unique fixed point of N.

The resulting t-norm enjoys the following rotation invariance property with respect to N:

T(x, y) ≤ z if and only if T(y, N(z)) ≤ N(x) for all x, y, z in [0, 1].

The negation induced by Trot is the function N, that is, N(x) = Rrot(x, 0) for all x, where Rrot is the residuum of Trot.

[edit] See also

[edit] References