1. Introduction
The author [
1] recently introduced algebraic Routley–Meyer-style (ARM for simplicity) semantics for basic substructural logics. Here, the term
ARM semantics means semantics with operations interpreting ternary relations, the frames of which have the same structures as algebraic semantics. This paper extends it to
fuzzy logics. To this end, we first recall some historical facts associated with Routley–Meyer semantics.
Using binary accessibility relations, Kripke [
2,
3,
4] first established relational semantics, the so-called
Kripke Semantics, for modal and intuitionistic logics. Since then, many semantics have been introduced as its generalizations. In particular, Urquhart provided operational semantics, called Urquhart semantics in [
1]; for relevant implication see [
5,
6,
7]. From an operational semantic point of view, this semantics is interesting since instead of binary relations for accessibility it has groupoid operations. More precisely, it provides the valuation of implication using the binary operation ∘ such that
- (→∘U)
if and only if (iff) for any , implies ,
instead of using the binary relation R such that
- (→RK)
iff for any , and imply .
Urquhart semantics has the following additional valuations for extensional conjunction and disjunction: For sentences ,
- (∧)
iff and ; and
- (∨)
iff or .
As is well known, these three valuation conditions do not work together for substructural logics in general. As Urquhart himself mentioned in [
7,
8], while sentences such as (
a)
are valid in their semantics, the distributive substructural logic
R of relevance does not prove such sentences. Because of this negative fact, Routley–Meyer [
9,
10,
11] instead introduced the so-called Routley–Meyer semantics for implication as a ternary relational semantics (see [
12]).
Please note that Urquhart [
7] provided the binary operational valuation for implication (
), whereas Fine [
13] did the following ternary relational valuation for implication.
- (→∘F)
iff for all , and imply .
Although these two valuations are not free from the above negative fact, they have been extensively used in substructural logics: Using (
), many logicians such as Do
en and Ono have introduced similar semantics for modal and substructural logics [
14,
15,
16]; with the title “Kripke-style semantics”, Montagna–Ono [
17], Montagna–Sacchetti [
18], and Yang [
19,
20] introduced similar semantics for substructural fuzzy logics. Using (
), logicians such as Ono–Komori [
21], Ishihara [
22], and Kamide [
23] have introduced analogous semantics for some (modal) substructural logics (For more detailed introduction of these semantics, see [
1]).
The starting point for the current work is the observation that, as the author [
1] mentioned, using ternary relation
, the valuations (
) and (
) can be rephrased as:
- (→RU)
iff for all
, if
(:=
(df
)) and
, then
, (We take
c in place of
in
because
. This was introduced by Dunn in [
24]) and
- (→RF)
iff for all
, if
(:=
(df
)) and
, then
, (As Do
en [
15] and Dunn [
25,
26] already mentioned, Fine [
13] interpreted
as
. Although Urquhart [
7] did not consider to reinterpret (
) using ternary relation, Bimbó and Dunn [
27] and Restall [
12] introduced such reformulation.), respectively.
In particular, using () and (), the author first introduced ARM semantics for basic substructural logics in general. Then, since fuzzy logics are also substructural logics and further prove sentences such as (a), one can ask the following.
- Q:
Could one establish ARM semantics, i.e., operational and ternary relational semantics equivalent to algebraic semantics, for basic substructural fuzzy logics, using the clauses (∧), (∨), and either () or () together?
As a positive answer to this question, we introduce such semantics with the conditions (∧), (∨) and the corresponding implication conditions for basic (core) fuzzy logics. (A logic L is called
fuzzy if it is complete on linearly ordered models, and
core fuzzy if it is fuzzy on
(see [
28,
29])). This will verify that the clauses (∧), (∨), and either (
) or (
) work together for basic substructural fuzzy logics.
The more detailed other reasons to study this are as follows: The first and most important reason is that while algebraic Kripke-style (briefly AK) semantics (The term
AK semantics means semantics with operations in place of binary accessibility relations, the frames of which have the same structures as algebraic semantics.) for substructural fuzzy logics have been introduced extensively (see, e.g., [
17,
18,
19,
20,
30,
31,
32]), ARM semantics for such logics have not. Only, the author [
33,
34] introduced such semantics for
MTL (Monoidal t-norm logic) and its involutive extension
IMTL. In particular, the author [
1] introduced ARM semantics for substructural logics in general, whereas he did not for substructural fuzzy logics. This is the direct specific reason to consider ARM semantics for
fuzzy logics in general.
The following are more reasons related to ARM semantics itself, some of which are mentioned in [
1]. First, “the definitions (df
) and (df
) provide more intuitive ways to understand or interpret the ternary relation
R. Please note that using the ternary relation
R in
itself we cannot say how to understand or interpret
R, whereas we can say it using
and
”. Second, this semantics provides a
direct way to understand
equivalence relations between algebraic and relational semantics. “An
n-ary operation is an
n+1-ary relation, but not always conversely. If one shows its converse, one can state an equivalence between the operation and the relation”. Associated with this, most well-known method to consider this equivalence is to use `canonical extensions’ investigated with the titles such as `representation’ and `duality’ (see [
35,
36,
37,
38,
39,
40,
41]). However, the way to use (df
) and (df
) is different from it and more direct in the sense that the way defines ternary relations by virtue of binary operations and (in)equations. The third is the fact that ARM semantics uses forcing relations. It means that this semantics is a study still in the tradition of relational semantic research. The last but not least one is that ARM semantics is a common area between algebraic semantics and ternary relational semantics. Since algebraic semantics and ARM semantics are both based on the same algebraic structures, this last semantics gives a chance to study similarities and differences between algebraic semantics and relational semantics.
We organize the paper as follows. In
Section 2, we first recall some basic (core) fuzzy logics, together with their algebraic semantics. In
Section 3, we introduce ARM semantics for them. More precisely, we introduce ARM semantics with (
) in
Section 3.1 and that with (
) in Sectio
Section 3.2. In
Section 4, we consider advantages and limitations of these two semantics as ARM semantics.
We finally note that, as in [
1], our ARM semantics in
Section 3.1 and
Section 3.2 provides frames as some reducts of their corresponding algebras and defines ternary relations using binary operations and (in)equations. However, unlike the semantics in [
1], this semantics is provided based on linear theories. More precisely, it is an ARM semantics with linearly ordered models. In this sense, this semantics is a
novel one to connect
n-nary operations and
n+1-nary relations. By
ARM semantics, we henceforth mean this kind of ARM semantics.
2. Algebraic Semantics for Basic Core Fuzzy Logics
Here we recall the most basic substructural core fuzzy logic
MIAL and its axiomatic extensions (extensions for short) and their algebraic semantics (See [
42] for more detailed introduction of these logics and semantics). The language for these logics is provided over a countable propositional language with
Fm (a set of formulas) built from
VAR (a set of propositional variables), propositional constants
t,
f,
,
, and connectives →, ⇝, ∧, ∨, &. We further define
and
as
and
, respectively.
The variables are denoted by lowercase Latin letters and the formulas by uppercase ones . Theories as sets of formulas are denoted by uppercase Greek letters . Please note that variables are also formulas. We provide a consequence relation, denoted by ⊢, on axiom systems.
Definition 1 ([
43,
44]).
MIAL consists of the axioms and rules below:, (∧-elimination, ∧-E);
(∧-introduction, ∧-I);
, (∨-introduction, ∨-I);
(∨-elimination, ∨-E);
(ex falsum quodlibet, EF);
(push and pop, PP);
(&-adjunction, &-Adj);
(&-adjunction, &-Adj);
();
(residuation, Res);
(residuation, Res);
(transitivity, T);
(transitivity, T);
(prelinearity, PL);
(prelinearity, PL);
(prelinearity, PL);
(prelinearity, PL);
, (modus ponens, mp);
(adj);
(α);
();
(β);
().
A logic is called an extension of a logic L if it is obtained from L by adding further axioms.
Definition 2. The following are basic structural axioms:
(exchange, e) ;
(expansion, p) ;
(contraction, c) ;
(left weakening, i) ;
(right weakening, o) ;
(associativity, a) .
MIAL, , is a substructural (core) fuzzy logic extendingMIAL
.
Example 1. The following well-known core fuzzy logics are extensions ofMIAL
.
- (1)
Micanorm logicMICALisMIALe.
- (2)
Uninorm logicULisMIALea.
- (3)
Monoidal t-norm logicMTLisMIALeai.
By s, we denote the set of substructural fuzzy logics introduced in Definition 2, i.e., s = .
A theory of ∈s (-theory for short) is a set of formulas such that entails . Since , the set of theorems of is a subset of all -theories. We define a proof in an -theory as a sequence of formulas, the elements of which are either axioms of , members of , or derived from its precedent elements using rules of . For each pair of formulas and a theory , if or , we call a linear theory.
Definition 3. Abounded, pointed residuated lattice-ordered groupoid with unit (-groupoid for simplicity) is an algebra = , ⊥, ⊤, 0, 1, ∖, /, , such that: is a unital groupoid; , ⊥, ⊤, ∧, is a bounded lattice; 0 is an arbitrary element in A; for all , iff iff (residuation).
Please note that the notations `∧’ and `∨’ are used both as propositional connectives and as algebraic operators.
Definition 4 ().
Let be . A -groupoid is aMIAL-algebra if it satisfies the following prelinearity properties: for all ,
(PL) ;
(PL) ;
(PL) ;
(PL) .
The following are the (in)equations corresponding to the structural axioms above: for all ,
() ;
() ;
() ;
() ;
() ;
() .
Thus, for any ,
MIAL-algebras are defined with S. We call all these algebras -algebras
and linearly ordered -algebras -chains.
Given an -algebra , an -valuation is defined as a map such that = (, …, , where #∈ {F, T, f, t, →, ⇝, ∧, ∨, &} and ∈ {⊥, ⊤, 0, 1, ∖, /, ∧, ∨, ∘}. A formula A is said to be an -tautology if for each -valuation v, . An -valuation v is said to be an -model of an -theory if for all . By Mod(Γ, ), we denote the class of all -models of . Over a class of -algebras, a formula A is called a semantic consequence of , denoted by , if for all . If is a semantic consequence of with respect to regarding {} whenever A is provable in on , is called an L-algebra. By MOD() and MOD(), we denote the set of such algebras and the set of linearly ordered ones, respectively, and write and instead of and , respectively.
Theorem 1 (). For a theory Γ over ∈s and a formula A, iff iff .
Proof. As a corollary of Theorem 3.1.8 in [
45], we obtain the claim. □
An -algebra is said to be standard if it has the real interval as its carrier set.
Theorem 2 ([
42]).
Let ε be a unit element in .- (i)
For ∈, iff for each standard-algebra and for each valuation v, for all implies .
- (ii)
For ∈ such that , iff for each standard-algebra and for each valuation v, for all implies .
Example 2. For {, , , , , , }, is not standard complete since (A) or (B) iff holds in standard -algebras but not in general in linearly ordered -algebras (see [42,46]). 3. ARM Semantics
In this section, we deal with the ARM semantics for fuzzy extensions of the basic substructural logics introduced in [
1]. As in [
1], we introduce two kinds of ARM
semantics: one is the semantics with the definition (df
) and linearly ordered models, called here
linear Urquhart-style Routley–Meyer semantics (briefly U-RM
semantics), and the other is the semantics with the definition (df
) below and linearly ordered models, called here
linear Fine-style Routley–Meyer semantics (briefly F-RM
semantics). Please note that unlike the semantics in [
1], these two semantics are provided using
linear theories in place of closed theories. However, these semantics still have the same structures as algebraic semantics and so are ARM semantics.
3.1. U-RM Semantics
Here we consider U-RM semantics for =. We first define several Routley–Meyer (RM for short) frames.
Definition 5. - (i)
(RM frames [1]) AnRM frame
is a structure such that 1 is a special element in F and . We call the elements of nodes.
- (ii)
(Linear RM frames) Alinear RM (briefly, RM) frameis an RM frame , where is a linearly order set.
- (iii)
((Residuated) Urquhart operational RM frames) AnUrquhart operationalRM (briefly, U-RM) frame is an RM frame , where ∘ is a groupoid operation satisfying (df) := . A U-RM frame is calledresiduatedif for any , the sets and have suprema.
- (iv)
(Bounded, pointed U-RM frames) AU-RM frameis said to bepointedif it further has an arbitrary element 0, andboundedif it further has top and bottom elements ⊤ and ⊥.
- (v)
(U-RM MIAL frames) AU-RM MIAL frameis a bounded pointed residuated U-RM frame, where ∘ is left-continuous and conjunctive and R satisfies the postulates below: for any ,
- p1.
- p2.
.
- (vi)
(U-RM frames) Consider the definitions and postulates below: for any ,
- df1.
)
- df2.
)
- pe.
implies .
- po.
iff , where ⊥ is the bottom element in F.
- pa.
iff .
For any ,U-RM MIAL framesare defined, along with their corresponding postulates. We call all these framesU-RM frames(briefly U- frames).
Remark 1. Definition 1 has some interesting facts to note.
- (1)
([1]) The definition of an RM frame in is the same as that of a frame structure forR (the positiveR), which eliminates all the definitions and postulates for the ternary relation R introduced in [8]. - (2)
The definitions in and are a fuzzy specification of partially ordered RM frames and (residuated) Urquhart operational RM frames introduced in [1]. (Please note that if ≤ is a partial ordering in place of a linear ordering in and , the definitions in and form partially ordered RM frames and (residuated) Urquhart operational RM frames introduced in [1].) - (3)
([1]) The postulates and in are for a unit element since we have that using (df). - (4)
([1]) The indices of the postulates in denote their corresponding axioms. For example, the postulate is for the exchange axiom e. In particular, (df) assures that the postulates satisfy the equational forms of their corresponding algebraic properties. For instance, using the postulate and (df), we have that , i.e., .
A valuation on a bounded pointed residuated U-RM frame is a forcing relation ⊩ between the nodes and the propositional variables, propositional constants, and formulas satisfying the below conditions. For each propositional variable p,
- (AHC)
and imply ;
- (min)
,
for the propositional constants , and F,
- (0)
iff ;
- (1)
iff ;
- (⊥)
iff , and
for formulas ,
- (→)
iff for all , and imply ;
- (⇝)
iff for all , and imply ;
- (∧)
iff and ;
- (∨)
iff or ;
- (&)
iff there exist such that , and .
A valuation on a U- frame is a valuation further satisfying that (max) for every propositional variable p, has a maximum.
Definition 6 (
U- model). An
U- model
is a pair , where is a U- frame and ⊩ is a valuation on . This model is said to be
complete
if is a complete frame and ⊩ is a valuation on .
Definition 7. For a U- model , a node a of and a formula A, a is said toforce Aif . A is said to betruein if , andvalidin the frame if A is true in for any valuation ⊩ on . For a class of U- frames and for a theory Γ, by , we mean that A is valid in whenever B is valid in it for all . This A is called asemantic consequenceof Γ on .
Now we consider soundness and completeness of .
Lemma 1 (Hereditary Lemma).
- (i)
Let be a residuated U- frame. For any formula A and for any nodes , if and , then .
- (ii)
Let ⊩ be a forcing relation on a U- frame and A be a formula. Then the set has a maximum.
Proof. It is easy to prove
. For the proof of
, see Proposition 3.3 in [
30] and Lemma 2.11 in [
18]. □
Lemma 2. iff for any , implies .
Proof. (⇒) See Lemma 3 in [
1]. (⇐) Suppose
and
and that
implies
. We prove
. Using the suppositions and (df
), we obtain that
and
; therefore,
. □
Theorem 3 (Soundness).For a linear theory Γ over L∈, a formula A, and a class of all U- frames, only if .
Proof. For the system MIAL, we consider the axiom as an example. For , by Lemma 2, we assume that and show that . This result directly follows from the supposition and the condition (⊥). The other axioms and rules for MIAL can be proved similarly.
For the other systems, we need to consider the other structural axioms, i.e., .
(e): Suppose that . We have to prove that . By the supposition and the condition (&), there are such that , , and . Then, and (df) ensure that and so . Hence, we obtain by (&).
(o): Suppose that . We have to prove . Please note that MIAL proves . Then, since and (df) assure that , we can obtain that using (⊥) and .
(a): Suppose . We have to prove . By the supposition, the condition (&), and (df), there are so that , , and ; therefore, for some , we have that , , and . Then, and so since , df1, df2, and (df) assure that . Since and , we may take some x so that and . Hence, by the condition (&), we obtain ; therefore, . The proof for the other direction is analogous. □
The following shows a connection between postulates for U- frames and algebraic (in)equations for the structural axioms of ∈.
Proposition 1. The postulates for U- frames introduced in Definition 1 as , , and are reducible to algebraic (in)equations , and , respectively.
Proof. We show that , , is reducible to .
(e): Using and (df), we obtain that for arbitrary , implies ; therefore, , i.e., , since .
(o): Using and (df), we obtain that iff for any and so , i.e., , since .
(a): Using , df1, df2, and (df), we obtain that for arbitrary , there is x such that and and thus iff and for some and so ; therefore, , i.e., . □
Corollary 1. Every U-, , frame is embeddable into a complete U- frame.
Proof. This corollary directly follows from Theorem 2 and Proposition 1. □
The next proposition connects algebraic semantics and U-RM semantics for .
Proposition 2. - (i)
The reduct of an -chain is a U- frame, which is complete iff is complete.
- (ii)
Let be a U- frame. Then, the structure = (F, ⊤, ⊥, , , , ∖, /, ∘) is an -algebra (where and are meant on ≤).
- (iii)
If is the reduct of an -chain and v is a valuation in , then is a U- model and for any formula A and for any , it holds that iff .
- (iv)
Let be a U- model and be the -algebra defined as in . Define for every propositional variable p, . Then, for every formula A, .
Proof. Here we consider
because the proof for
and
is easy and
follows almost directly from
and Lemma 1
. We consider the induction steps, where
and
. For the induction step of
, see Proposition 3.9 in [
33]. The proof for the other cases is easy.
Suppose . By the condition (→), iff for any , and entail , hence by the induction hypothesis, iff for any , and entail and so iff ; therefore, iff by residuation. The proof for the case is analogous. □
Theorem 4 (). Let Γ be a linear theory on ∈ , A a formula, and a class of all U- frames.
- (i)
iff.
- (ii)
Let ∈ , eq′ = , and
a class of all complete U- frames. Then,
iff
Proof. follows from Proposition 2 and Theorems 1 and 3 and from Proposition 2 and Theorems 2 and 3. □
Example 3. Among the examples introduced in Example 1, the systemsMICALandULhave U-RM semantics butMTLdoes not since the postulates are equationally definable by (df) but the postulate i is not. Therefore, we can say the following.
- (1)
Micanorm logicMICALhas a U-RM semantics.
- (2)
Uninorm logicULhas a U-RM semantics.
- (3)
Monoidal t-norm logicMTLdoes not have a U-RM semantics.
Please note that one is capable of defining the ternary relation R using (df) and the forcing relation ⊩ using ≤. This means that for ∈ , U-RM semantics can be considered in the context of algebraic semantics and vice versa.
As in [
1], using the definition (df
) and the valuation conditions (→) and (⇝), we can show the following derived conditions of a valuation.
Proposition 3 - (1)
For any , implies iff for any , and imply .
- (2)
For any , implies iff for any , and imply .
Proposition 3 ensures that, as far as we accept (df), the conditions of a valuation are reducible to those of AK semantics for . Thus, U-RM semantics for can be reduced to the AK semantics for with the definition (df). Therefore, this semantics can be called ARM semantics reducible to AK semantics.
3.2. F-RM Semantics
Here we consider F-RM semantics for s. We first define some further RM frames.
Definition 8. - (i)
(Operational RM frame [1]) An operational RM frame
is a structure , where is an RM frame, is a groupoid with unit, and R satisfies the postulates below: for all , - ps.
and imply ;
- pt.
and imply ;
- p≤.
iff .
- (ii)
((Residuated) Fine operational RM frame) Linear RM frames are defined as in Definition 5. AFine operationalRM frame (F-RM frame for short) is an operational RM frame, where ∘ satisfies (df) := (Notice that ≤ in (df) is considered order reversely. Please compare it with ≤ in (df).) and R satisfies the postulate below: for all ,
Residuated F-RM frames are defined as in Definition 5.
- (iii)
(Bounded, pointed F-RM MIAL frames) Bounded, pointed F-RM frames are defined as in Definition 5. AnF-RM MIAL frameis a bounded pointed residuated F-RM frame, where ∘ is conjunctive and left-continuous.
- (iv)
(F- frames) Consider the definitions and postulates df1, df2, , , and the below additional postulates: for all ,
- pp.
implies .
- pc.
- pi.
implies .
For any ,F-RM MIAL framesare defined, along with their corresponding postulates. We call all these framesF- frames.
Remark 2. - (1)
One is capable of showing that (F, ≤) is a linearly ordered set, using (df), identity , , , and in F-RM frames and so these frames are linearly ordered.
- (2)
([1]) The indices of the postulates in denote their corresponding axioms. For example, the postulate is for the expansion axiom p. Moreover, (df) assures that those postulates satisfy their corresponding algebraic properties.
The conditions for a valuation on an F-
frame are the same as in
Section 3.1 except for the following:
- (&R)
iff there exist so that , and .
We can prove Proposition 3 and the condition (&) using (df). Moreover, we can further show the following additional derived condition.
Proposition 4. iff there exist such that , and .
Proof. (⇒) Assume that . We take satisfying that and . Then, using (df), we can obtain that , , and . (⇐) Suppose that , and . Then, using (df), we obtain , , and ; therefore, . □
Notice that Lemmas 1 and 2 also hold for F- frames and models.
Theorem 5 (Soundness)For a linear theory Γ over L∈s, a formula A, and a class of all F- frames, only if .
Proof. We need to consider the structural axioms . For c, we assume that and show that . By the supposition, , and (&), we obtain that . The proof for the other ones is analogous. □
Now, we recall a connection between postulates for F- frames and algebraic (in)equations for the structural axioms of ∈s.
Proposition 5 ([
1]).
The postulates for F- frames introduced in Definition 1 are reducible to algebraic (in)equations for the structural axioms of introduced in Definition 4. The next proposition connects F-RM semantics and algebraic semantics for s.
Proposition 6. - (i)
The reduct of an -chain is an F- frame, which is complete iff is complete.
- (ii)
Let be an F- frame. Then, the structure = (F, ⊤, ⊥, , , , ∘, ∖, /) is an -algebra.
- (iii)
If is the reduct of an -chain and v is a valuation in , then is an F- model and for all formulas A and for all , we obtain that iff .
- (iv)
Let be an F- model and be the -algebra defined as in . Define for every propositional variable p, . Then, for every formula A, .
Proof. As above, we prove . We consider the induction steps, where , and , since the other cases can be easily proved.
Suppose . The condition () assures that iff there are so that , and , hence by the induction hypothesis and (df), iff there are such that , and . It then holds true that . Conversely, suppose and take and . Then we can obtain , and ; hence, by () and (df).
Suppose . The condition (→) assures that iff for all , and entail , hence by the induction hypothesis and (df), iff for all , and entail . Then, we obtain since . Suppose conversely that . Then we have that and so for and . This ensures that and entail ; hence, by (→).
The proof of the case is analogous to the case . □
Theorem 6 (). Let Γ be a linear theory over ∈ s, A a formula, and a class of all F- frames.
- (i)
iff .
- (ii)
Let be a member of or such that , and a class of all complete F- frames. Then, iff .
Proof. follows from Proposition 6 and Theorems 1 and 5 and from Proposition 6 and Theorems 2 and 5. □
Example 4. All the systems introduced in Example 1 have F-RM semantics since the postulates are inequationally definable by (df). However, the non-fuzzy systemR (the positiveR) does not have such semantics since, while F-RM semantics validates sentences such as in Section 1, R does not proves such sentences. Therefore, we can say the following. - (1)
Micanorm logicMICALhas an F-RM semantics.
- (2)
Uninorm logicULhas an F-RM semantics.
- (3)
Monoidal t-norm logicMTLhas an F-RM semantics.
- (4)
The positive relevance logicR does not have an F-RM semantics.
As above, one is capable of defining the ternary relation R using (df) and the forcing relation ⊩ using ≤. This means that for ∈s, F-RM semantics can be considered in the context of algebraic semantics and vice versa.
5. Discussion and Conclusions
We investigated ARM semantics for substructural (core) fuzzy logics based on mianorms. More precisely, we provided U-RM and F-RM semantics as two sorts of ARM semantics for them. We in particular deal with advantages and limitations of these semantics.
We note that U-RM
and F-RM
semantics provide frames as some reducts of their corresponding algebras and so are ARM
semantics for fuzzy extensions of substructural logics. Especially, those semantics define ternary relations using binary operations and (in)equations like the semantics for substructural logics in [
1]. However, unlike these semantics, they are provided based on linear theories and conditions for linear ordering, and so work for linearly ordered models. As mentioned in
Section 1, ARM
semantics as a relational semantics for substructural fuzzy logics in general is a
novel one to connect
n-nary operations and
n+1-nary relations.
The author [
47] introduced implicational tonoid
fuzzy logics as fuzzy extensions of implicational tonoid logics, the class of logics satisfying transitivity, reflexivity, tonicity, and modus ponens introduced by the author and Dunn [
48]. Please note that all the logic systems introduced in Definition 2 can be regarded as such fuzzy logics because they also satisfy the conditions for an implicational tonoid logic and are complete over linearly ordered models. Hence, this investigation can be thought of as an introduction of ARM semantics for
concrete implicational tonoid fuzzy logics.
However, any more exact connection between semantics for implicational tonoid fuzzy logics and those for substructural (core) fuzzy logics is not studied here. For instance, while the former logics do not introduce any concrete connectives, the substructural (core) fuzzy logics do. For these logics, the connectives ∨ and ∧ need to be interpreted by
and
as lattice operators and need their corresponding relational consideration. Thus, in the context of implicational tonoid fuzzy logics, these things have to be dealt with. Furthermore, while non-operational RM semantics can be established for substructural logics, e.g., the system
R (see [
8]), such semantics for the fuzzy logics is not considered either. The author has a plan to study these two in the future, i.e., leave these for another day. By these two works, we can fill gaps between abstract logic (implicational tonoid fuzzy logics) and concrete logic (substructural (core) fuzzy logics) and between algebraic and non-algebraic Routley–Meyer-style semantics.
It is well known that lattices can be defined as ordered sets and as algebraic structures. To show the equivalence between the first relational definition of a lattice and its second algebraic definition, one has to have some definitions such as
iff
iff
. Similarly, we can consider the algebraic and ARM semantics and the definitions (df
) and (df
) regarding substructural (core) fuzzy logics. Associated with this, the author [
49] studied basic logico-algebraic properties of micanorms characterizing the logic
MICAL such as (left-)continuity, residuated implications, conjunctive and disjunctive micanorms, idempotent, nilpotent, and divisor micanorms, and so on. This implies that such theoretic applications of micanorms can be considered in the context of U-RM
and F-RM
frames. Namely, one can treat such properties as applications of U-RM
and F-RM
frames. More exact treatment of such applications is an another problem to solve in the future.