Metric Linear-Time Temporal Logic with Strict First-Time Semantics
Abstract
We introduce strict first-time semantics for the Until operator from linear-time temporal logic which makes assertions not just about some future moment but about the first time in the future that its argument should hold. We investigate Metric Linear-Time Temporal Logic under this interpretation in terms of expressive power, relative succinctness and computational complexity. While the expressiveness does not exceed that of pure LTL, there are properties definable in this logic which can only be expressed in LTL with exponentially larger formulas. Yet, we show that the complexity of the satisfiability problem remains PSPACE-complete which is in contrast to the EXPSPACE-completeness of Metric LTL. The motivation for this logic originates in a study of the expressive power of State Space Models, a recently proposed alternative to the popular transformer architectures in machine learning.
Keywords and phrases:
linear-time temporal logic, metric temporal logic, computational complexity, Streett automataCopyright and License:
2012 ACM Subject Classification:
Theory of computation Modal and temporal logics ; Theory of computation Automata over infinite objectsEditors:
Thierry Vidal and Przemysław Andrzej WałęgaSeries and Publisher:
Leibniz International Proceedings in Informatics, Schloss Dagstuhl – Leibniz-Zentrum für Informatik
1 Introduction
The linear-time temporal logic LTL is a well-known formalism for specifying properties of runs of reactive systems [14]. Its model-theoretic and computational properties are well researched and understood, for instance its satisfiability problem being PSpace-complete [17] and its expressiveness coinciding with that of First-Order Logic [6], resp. star-free regular expressions over -words or over finite words [7].
The relative weakness in expressive power has led to the study of several extensions of LTL, some of which genuinely extend its expressiveness, typically to that of full (-)regularity, for instance the Linear-Time -Calculus [3, 19], the industry standard PSL [5], Quantified LTL [16], etc. Others extend LTL only pragmatically by providing further constructs without extending the expressive power altogether, but providing means to express certain properties more easily.
One such variant is the Metric Linear-Time Temporal Logic MTL [1]. The term “metric temporal logic” does not uniquely identify one particular formalism, not even within the linear-time framework. It describes temporal logics in which the temporal operators are extended so that they do not simply make assertions about the future (or past) moments in a linear sequence of events, but additionally constrain their distance to the current moment. For example does not only demand that holds at some point in the future with being continuously true up to that point, but this future point also has to occur within three to five time units from now on. The exact semantics then depends on the underlying models etc. Metric temporal logic has been developed for reasoning about real-time systems [9], but it can also be used for systems evolving in discrete steps. Here we use MTL only as a logic over discrete time, resp. (untimed) -words. Consequently, the intervals adorning the metric operators are always interpreted over the natural numbers.
It is not hard to see that MTL does not exceed LTL in expressiveness: temporal operators with metric constraints can easily be unravelled. The property above can be expressed as “ holds now and in the next two steps; afterwards we have or followed by or followed by another , followed by ” using only the next-time operator (in this case). A general translation from MTL to LTL is an easy exercise, and it incurs a blow-up that is polynomial in the value of the involved interval bounds. Hence, when such bounds are encoded unarily, MTL satisfiability is also PSpace-complete. The more reasonable assumption of binary encodings then yields an exponential translation into LTL and therefore an ExpSpace upper bound on its satisfiability problem. This is tight, satisfiability for MTL with binarily encoded interval bounds is in fact ExpSpace-complete [10].
The lower bound uses a standard reduction from the word problem for exponentially space bounded Turing Machines (TM). The key to the proof is then MTL’s ability to express “something holds after steps” which, using binary encodings, can be done with a formula of size polynomial in . This is used to express, for instance, that a symbol is seen at that distance, i.e. at the same cell on the tape in the next configuration, formalising a potential writing operation of the TM. Clearly, the tape may contain more occurrences of that symbol, so the one seen at distance is usually not the first one to be seen in the future.
This paper is motivated by the study of the expressive power of a recent machine learning model, so-called State-Space Models (SSM) [13]. They have been proposed as an alternative to the well-known transformer architectures underlying prominent Large Language Model tools, promising more efficient evaluation of long input strings. Here we do not go further into the details of SSMs; they merely serve as a motivation for studying a particular variant of MTL which is geared towards the expressive capabilities of SSMs. To motivate this variant, we recall the well-known unfolding principles for temporal operators.
Example 1.
Suppose that, in the context of some decision procedure, we were to establish the truth of the LTL formula at position of some -sequence of events. By unfolding the -operator, this typically amounts to establishing truth of both (i) and (ii) at moment . To solve (i) we can either prove or defer it to a later point by unfolding the Until-formula and proving as well as (iii) at moment . Now, (ii) and (iii) both start with a Next-operator, so they imply proving and (iii’) at moment . The former can be handled as done at moment ; in particular it means proving at moment which is already the task identified as (iii’). In a sense, there are two reasons for the need to prove at moment , and they just collapse to a single task.
Now suppose that the original formula was one of MTL, namely . Here the reasoning can be done in the same way, but when unfolding the metric Until we obtain an index shift: is established at moment when is established there. Hence, when carrying out this kind of reasoning we obtain two tasks regarding moment that do not collapse into one, namely to prove as well as there.
This can also be seen as an indication for MTL’s higher complexity: truth of a formula at moment does not just depend on the truth of its subformulas at moments and , but also on variants of the subformulas obtained through index shifts.
The mechanisms in SSMs naturally suggest a comparison of their expressiveness with formulas of metric linear-time temporal logic (on finite words), since SSMs can easily track the distance between occurrences of events in a word, they seem to be unable to cope with the blow-up in formulas that need to be tracked through unfolding.
In this paper we initiate the study of a variant of MTL– called Metric Temporal Logic with Strict First-Time Semantics here, MTL1– which is defined because of a certain similarity to the mechanics in SSMs. It features the Metric Until operator which does not just demand that some future moment at distance between and satisfies , but this also has to be the first time (from the current moment on) that is satisfied. Note that this remedies the problem with a potential blow-up indicated by the example above: while cannot be simplified into a formula using only a single metric Until operator, is indeed equivalent to , suggesting that the strict first-time semantics makes formulas easier to handle computationally. It is also not hard to see that the proof of ExpSpace-hardness for MTL breaks down under the strict first-time semantics, as suggested above. So apart from the obvious question about MTL1’s expressiveness in relationship to the other variants of LTL, its complexity somewhere between PSpace and ExpSpace is to be pinpointed as well. An ExpSpace upper bound is obtained easily because of a simple linear translation into MTL, based on principles like .
This paper is organised as follows. In Section 2 we formally recall known concepts needed for this study, in particular LTL and its extension MTL. We also recall the definition of Streett automata [18] which will serve as a main tool in a decision procedure for MTL1 which is formally introduced in Section 3. There, we also investigate its expressiveness and succinctness relative to LTL. In Section 4 we construct a singly exponential translation from MTL1 into Streett automata thus pinpointing the former’s complexity as being PSpace-complete only. In Section 5 we conclude with remarks on further work in this area.
2 Preliminaries
We recall the necessary definitions from temporal logics and automata theory.
Linear-time temporal logic.
Let be a non-empty, countable set of atomic propositions. Formulas of the linear-time temporal logic LTL are given by the following grammar.
where . Further Boolean operators like are introduced as abbreviations in the usual way, and so are the temporal operators , , .
The set of subformulas of is defined in the usual way. The size of a formula is measured in terms of the number of its subformulas: . For our purposes here, it makes no difference whether formulas with abbreviated operators are written out in the original syntax or the abbreviated operators are seen as first-class citizens. The size in the former case is only larger by a constant factor compared to the latter case.
Formulas of LTL are interpreted over traces of labelled transition systems which are just -words over the alphabet . Note that any formula can contain only finitely many propositional symbols. Hence, the alphabet underlying any given formula can always be assumed to be finite. Let and . Satisfaction of an LTL formula in at position is explained inductively as follows.
| iff | ||||
| iff | ||||
| iff | ||||
| iff | ||||
| iff |
A word satisfies a formula , written , if is satisfied in its initial position, i.e. . The language of a formula is the set of all words satisfying it: . Two formulas are equivalent, written , when their languages coincide, i.e. . Note that this is the case if and only if they are satisfied by exactly the same positions in the same words, i.e. iff . The “if”-direction is trivial because two formulas that are satisfied by the same words at arbitrary positions are clearly satisfied by the same words at initial positions. The “only if”-direction holds because LTL has future-only operators, so we have iff for any . Thus, any position in a word is the initial position of another word, namely the suffix starting at this position.
A formula is valid, written , if , i.e. it is satisfied by any word. The satisfiability problem – given a formula , decide whether – is well-known to be decidable. We write for the satisfiability problem for logic . We assume familiarity with standard complexity classes, in particular the space complexity classes NLogSpace, PSpace and ExpSpace. For further details we refer to standard textbooks in complexity theory, e.g. [2].
Proposition 2 ([17]).
SAT(LTL) is PSpace-complete.
Metric linear-time temporal logic.
The term “metric” temporal logic usually refers to extensions of ordinary temporal logics (like LTL) with modifications of the temporal operators that impose restrictions on the moments that witness their satisfaction in case of an Until or a Finally, resp. relax the future moments under consideration of a Generally, resp. Release formula. The logic MTL is obtained by extending the syntax of LTL with a metric version of Until, written for a non-empty interval over the natural numbers.
We use standard notation for closed, half-open and open intervals like and for with . Because of the discrete nature of and the lack of a direct predecessor of in this structure, we can restrict our attention to intervals of the form for , and of the form for . Note that etc.
Intervals of the form or for some are called simple and written more compactly as , resp. .
The semantics of formulas of MTL is extended accordingly for words and by
Hence, note only requires a position in to satisfy in the usual sense that some future moment satisfies and all future moments before that satisfy . It additionally requires that future moment to be found at a distance which falls into the interval .
This clearly extends the non-metric version of LTL because . The metric extension is then applied to the other derived temporal operators and accordingly.
Because of the use of natural numbers as interval bounds in temporal operators, number of subformulas is not a realistic measure of the representation size of a formula anymore. Note that , stating that occurs in a word at some distance between and would have constant size regardless of the values of and . We assume that such interval bounds are given in binary encoding and therefore measure the size of a formula more appropriately as follows. Let
denote the largest integer constant that is used as an interval bound in a subformula of . Then .
Proposition 3 ([10]).
SAT(MTL) is ExpSpace-complete.
Finite automata on -words.
Let be a finite set of atomic propositions. A nondeterministic Streett automaton (NSA) is an where is a finite set of states, is the designated initial state, is a finite set of transition triples with denoting the set of Boolean formulas over (with the usual Boolean operators , , , …). Finally, with for all is the acceptance condition.
Note that here such finite automata have a symbolically represented transition table instead of the general for a finite alphabet . The reason for this choice is their use in a decision procedure for a temporal logic whose formulas are naturally interpreted over -words whose letters are finite sets of propositions, i.e. . Instead of enumerating all such possible sets and explaining the automaton’s one-step behaviour for each step, the symbolic representation here is more convenient for such special cases. There are straightforward translations for the transition relations between symbolic and explicit representations, and for a fixed set of propositions, they are polynomial. Hence, we can safely use Streett automata in this form and still appeal to known results about them, even though they were perhaps formulated for the form with an explicit alphabet.
A run of the NSA with on a word is a such that and for all there is some such that , and . Here, satisfaction of a Boolean formula over by a set , , is explained in the usual way: evaluates to true when all are set to true and all are set to false.
We write to denote the set of all states that occur infinitely often in . By finiteness of , we always have .
The run is accepting if it satisfies the Streett condition in the sense that for all : if then . As usual, is the language of the NSA , and it consists of all words on which has an accepting run.
So both NSA and formulas of linear-time temporal logics defines languages of -words which is why these different formalisms can be compared to one another in terms of expressiveness, and satisfiability of a formula corresponds to non-emptiness of the language of an automaton. Algorithms for non-emptiness problems for -automata are routinely used to obtain decision procedures for linear-time temporal logics [21, 20, 4]. It has been shown that non-emptiness for Streett automata can be decided in polynomial time [8, 12] and this requires an explicit construction. A polynomial (equivalence-preserving) translation into Büchi automata is not possible, let alone one computable in logarithmic space. This would immediately transfer the upper bound of NLogSpace to Streett automata. Nevertheless, it does hold, too; it simply needs to be shown directly.
Theorem 4.
The non-emptiness problem for NSA is decidable in NLogSpace.
Proof.
The key observation is the following. The language of an NSA with and is non-empty iff there is an ultimately periodic word . This follows from finiteness of and by the pigeon hole principle. An accepting run on an arbitrary word must eventually traverse a state for the second time such that in between, for every , either no state from or some state from has been seen.
This gives rise to a nondeterministic algorithm for deciding non-emptiness. It guesses, step-by-step, the states of a run and also nondeterministically remembers some state occurring in this simulation. It then maintains bits to remember, for each , whether some state in and some state in has been seen. It accepts, when occurs again, and the bits indicate that the Streett condition has been met in between.
In order to terminate and reject on computation paths with unsuccessful guesses, it counts the number of steps done in this simulation. It is not hard to see that the first occurrence of can be required to occur after at most steps. The second occurrence can be expected to occur after no more than a further steps, for otherwise the run contains parts that could be skipped. Hence, the space needed for the counter is at most logarithmic in .
3 Metric LTL with First-Time Semantics
Syntax and Semantics.
We introduce Metric Linear-Time Temporal Logic with Strict First-Time Semantics (MTL1) which, instead of metric Until formulas of the form , features a special modification that is interpreted under strict first-time semantics. Intuitively, it does not just demand that some occurrence of in the future happens at a distance that falls into the interval . Instead, it requires this to be the first time in the future that this happens.
Definition 5.
Let be a non-empty, countable set of atomic propositions as usual. Formulas of the linear-time temporal logic MTL1 are built according to the following grammar.
where and is an interval over as discussed above.
We also introduce its fragment sMTL1– Simple MTL1– which only features simple intervals or in its formulas. Other Boolean and temporal operators, in particular the strict first-time variants , and are introduced as abbreviations in the usual way. The set of subformulas of an MTL1 formula is defined as usual by induction over the syntax tree of the formula.
The intuition behind the restriction to first-time occurrences is made formal as follows.
Definition 6.
Let be given as above and . Satisfaction of an MTL1 formula at a position of the word is explained inductively over the structure of as for LTL, apart from the following case.
Expressiveness.
LTL trivially embeds into sMTL1 which trivially embeds into MTL1. The reason for this is the fact whenever an Until-formula gets satisfied somewhere then there is also a first time that this happens. A more interesting question concerns the other direction, and therefore also the connection to MTL. Since LTL can trivially be embedded into MTL, we immediately obtain a translation from MTL1 into MTL, from one from MTL1 into LTL.
We remark that the translations introduced in the following are not polynomial for formula length, measure in terms of length of string representations, but only for formula size, measured in terms of number of subformulas, as they often require the duplication of subformulas.
The first observation about expressiveness is the expressive equivalence between MTL1 and sMTL1. This is perhaps a little bit surprising as this principle does not apply to MTL.
Theorem 7.
For every there is a of size such that .
Proof.
We can define inductively. The only non-trivial case is that of an Until formula. Then we have
for . Clearly, this increases the number of subformulas at most by factor . Correctness of this translation is straightforward by inspection of the semantics.
Because of Thm. 7 we can restrict our attention to sMTL1 formulas down below as this simplifies the technical details of various constructions slightly.
One reason for considering numerical values in formulas to be represented in binary (as opposed to unary), apart from this being natural, is the fact that the expressive power of sMTL1– and that of MTL in fact – does not exceed that of LTL. However, translations back into LTL are polynomial in the value of interval bounds only, i.e. they are in fact exponential in the size of a formula.
Theorem 8.
For every sMTL1 formula there is an LTL formula such that and .
Proof.
We define a translation as follows.
The translation of an operator clearly produces a formula whose size is linear in the
value , i.e. exponential in the representation size of . Replacing the abbreviated biased disjunctions
by plain Boolean formulas only incurs a further polynomial blow-up because formula size is measured in terms
of number of subformulas.
Correctness of the translation is proved by a straightforward induction on the structure of , showing that for all and all , we have iff .
Succinctness.
The exponential blow-up predicted by Thm. 8 may seem like a downside at first sight. However, it should be read as the possibility that certain properties, which are definable in LTL, can be defined in sMTL1 with much shorter formulas. The same phenomenon is of course known from LTL. It is easy to show that every family of LTL formulas equivalent to the MTL formulas require size . The proof can be re-used entirely to show that sMTL1 is also exponentially more succinct than LTL. Note that .
Theorem 9.
There is a family of LTL-definable languages over a singleton such that each is expressible in sMTL1 by a formula of size but every family of LTL formulas with is such that .
Proof.
Consider the sMTL1 formulas for . Clearly, . By a standard induction on the structure of LTL formulas we can show that formulas of size cannot distinguish between the two words and . Since but for all , we get that any presumed LTL-formula equivalent to needs to have size at least.
4 An Automata-Theoretic Decision Procedure
We give an automata-theoretic decision procedure for MTL1. Decidability of its satisfiability problem is not a surprise in the light of Thm. 8, stating that sMTL1– and therefore also MTL1 according to Thm. 7 – can be translated into LTL at an exponential blow-up. This is unavoidable according to Thm. 9. Then it is perhaps rather surprising that the complexity of MTL1 is asymptotically no worse than that of LTL. We give an upper bound of PSpace, based on a translation into Streett automata. According to Thm. 8, it suffices to do so for sMTL1.
Temporal formulas and their unfoldings.
For convenience, we work with sMTL1 formulas in negation normal form (NNF), i.e. those that are built from literals using the Boolean operators and the temporal operators and where . The following is a standard observation about the ability to push negations inwards in formulas to obtain NNF.
Lemma 10.
For every sMTL1 formula there is an sMTL1 formula in NNF of size such that .
The construction of a Streett automaton recognising for some sMTL1 formula in NNF then follows the same principles as the standard construction of a Büchi automaton for an LTL formula. Temporal operators are typically handled by unfolding, not just in automata-theoretic decision procedures. The term denotes the two equivalences
These can be extended to the temporal operators in sMTL1 as follows. The proof is just by close inspection of the semantics of MTL1.
Lemma 11.
Let , . We have
A formula of the form on one of the left-hand sides in these equations is called a temporal formula and we use to denote the corresponding right-hand side. Temporal formulas of the form , i.e. Until-formulas whose metric parameter is a half-open interval to the right, are called critical.
Later on we will need a second observation about temporal formulas. The proof is straightforward from an inspection of the semantics of MTL1. The lemma already holds for MTL in fact.
Lemma 12.
Let be sMTL1 formulas and such that . Then we have
The Fischer-Ladner closure of a formula is a collection of all subformulas and perhaps others derived from them that may play a role in determining the truth of at some point in a word.
Definition 13.
Let be in NNF. Its Fischer-Ladner closure is the least set that contains and is closed under the following operations.
-
If or then .
-
If then .
-
If for a temporal , then .
The key concept in an automata construction for sMTL1 formulas is that of a Hintikka set – a set of formulas that is closed under propositional logic consequence. We need to refine the standard definition slightly in order to obtain the intended complexity bound in the end.
Definition 14.
Let be in NNF. A is called a Hintikka set for if it satisfies the following conditions.
-
If then .
-
If then .
-
If for a temporal then .
is called (propositionally) consistent if there is no such that . It is called lean if for all there is at most one temporal formula for any , and likewise for temporal formulas of the three other forms with operators , and . We write , resp. for the set of all lean, propositionally consistent Hintikka sets for , resp. those that are additionally lean.
While the Fischer-Ladner closure of an formula is generally exponential in and there are, thus, doubly exponentially many Hintikka sets, there are only singly exponentially many lean Hintikka sets.
Lemma 15.
Let be in NNF. Then .
Proof.
Note that there are at most many formula schemes, i.e. members of modulo concrete metric parameters. A lean set can then be seen as a mapping for each such formula scheme to a value in , indicating (non-)inclusion in the set and giving a concrete parameter value for a temporal formula. Since due to binary encoding, there are at most many lean (Hintikka) sets.
Streett automata for sMTL1 formulas.
We are now in a position to define a Streett automaton of singly exponential size that recognises exactly the models of an sMTL1 formula in NNF.
Fix an sMTL1 formula in NNF over some finite . We will need three constructions on (lean) Hintikka sets for . The first one collects all literals in a lean Hintikka set.
It can be seen as the extraction of a propositional formula determining the letter at a position in a word where all formulas in are supposed to be true. On the other hand,
collects all “leanifications” of Hintikka sets that are potential successors to in the sense that they contain all formula which needs to be true at the next position. The leanification of is obtained by successively replacing temporal formulas as follows until no further steps are applicable.
-
If or for some and then replace all occurrences of the latter that do not occur under the scope of a -operator by the former.
-
If or for some and then replace all occurrences of the former that do not occur under the scope of a -operator by the latter.
It should be clear that is indeed a set of lean Hintikka sets for .
The important observation about the leanification process is the preservation of the semantics in a strong sense.
Lemma 16.
Let be in NNF and . For every there is such that differs from only in the values of metric parameters and .
Proof.
This is proved in a straight-forward induction on the structure of . The only non-trivial cases are those of temporal formulas. These are covered by Lemma 12. Since leanification also replaces subformulas, we also need the fact that (and all its subformulas) are given in NNF. Hence, if then also for any , i.e. all formulas are monotonic.
The acceptance condition of the NSA is determined by the set of all critical temporal formulas that can occur in lean Hintikka sets for . However, unfolding decreases interval bounds by one, so the number of critical temporal formulas in is exponential: if contains the subformula for some , then contains for all , i.e. exponentially many in because of binary encodings of interval bounds.
The exact interval bounds are irrelevant for the acceptance condition. It is only used to ensure that no critical temporal formula gets unfolded forever without ever satisfying its right argument . We introduce the notion of a critical formula scheme and write if there is some such that .
Note that there is no need to treat the other three kinds of temporal formulas in the same way. A temporal Release-formula is a greatest fixpoint, and unfolding it infinitely often is a legitimate way of determining its truth. A non-critical, temporal Until-formula of the form cannot get unfolded infinitely often because each unfolding step decreases the metric parameter in it until it eventually becomes , and the formula is replaced by anyway. Note that this is not the case for critical Until-formulas. Unfolding them still decreases the metric parameter. However, the leanification process can increase it again, whereas leanification for non-critical Until-formulas can only decrease it further.
Let be the set of all schemes of critical temporal Until-formulas in , i.e. for some . We define the NSA as where
-
,
-
,
-
with and . Note that may contain other temporal formulas, so is to be understood as a scheme potentially, and means that some formula deviating from in metric parameters only is contained in .
The next two lemmas are devoted to the soundness and completeness of the construction.
Lemma 17.
Let over be in NNF and as above. Then .
Proof.
Let be such that there is an accepting run of on . By the construction of we have (i) and, for all , (ii) and (iii) there is such that for all and .
We show by induction on the structure of formulas that for all and all we have . For literals or this follows immediately from (ii). For conjunctions and disjunctions this follows by the hypothesis for both conjuncts, resp. one disjunct and the fact that each is a lean Hintikka set that behaves like a Hintikka set in this case, i.e. it contains both conjuncts of a conjunction etc. This is the case because leanification replaces either none or all occurrences that are not under the scope of a -operator. Hence, a replacement takes place in a conjunction iff it takes place in both conjuncts etc.
Suppose is of the form . Because of (iii), there is a with with . According to Lemma 16, there is that is structurally not greater than . Hence, we can apply the induction hypothesis to it and obtain . According to Lemma 16, we then also have and therefore .
Suppose is of the form . By inspection of the unfolding rule (Lemma 11) and successive applications of the principles (ii) and (iii) with the same kind of reasoning using Lemma 16, we get some and a sequence of Hintikka sets such that , for some with and for some such that . Applying the induction hypothesis to at position and for at positions shows that these are satisfied at the respective positions in . Lemma 16 then yields and for all . Thus, .
Suppose is of the form . Note that it is a critical temporal formula in this case. We can apply the same reasoning as in the previous case using Lemmas 11 and 16. However, here the leanification process may replace metric parameters by larger ones. Hence, this alone does not guarantee the existence of a such that . This is where ’s acceptance condition comes into place. Since is accepting, it must either contain finitely many lean Hintikka sets containing or infinitely many containing . The latter case immediately implies the existence of such a . The former case does so, too, by inspection of Lemma 11 and the construction of Hintikka sets. It is only possible to have (the scheme) finitely often only when some contains and therefore also . The rest of this case is handled as the previous one.
The remaining two cases of temporal Release-formulas are also handled in a way that is analogous to those of the Until-formulas.
At last, (i) says that . By the reasoning above we then have , i.e. which completes the claim.
Lemma 18.
Let over be in NNF and as above. Then .
Proof.
Suppose . We need to construct an accepting run of on . To this end, we construct a sequence via . It is not hard to see that each is indeed a propositionally consistent Hintikka set. Moreover, if then . This therefore determines a sequence of lean Hintikka sets by leanification: for all , forming a run .
It remains to be seen that it is indeed an accepting run. Take some critical Until-formula scheme and suppose that contains an infinite subsequence with for all . By construction, we have . By the semantics of MTL1 there are with such that and, again, by construction . Since , the set is infinite. Hence, the sequence has an infinite subsequence in which every Hintikka set contains . Then the run has an infinite subsequence in which every lean Hintikka set either contains itself or an instantiation of the scheme . In any case, the run satisfies the Streett pair associated with . Since this is the case for any critical , is indeed accepting and so we have .
Putting all of the above together we obtain that MTL1 is not just decidable but that its satisfiability problem is no worse than that of ordinary LTL (and therefore exponentially easier than that of MTL), even though there is an exponential succinctness gap between MTL1 and LTL.
Theorem 19.
SAT(MTL1) is PSpace-complete.
Proof.
The lower bound is straightforwardly inherited from LTL. For the upper bound, note that every MTL1 formula can be translated into an equivalent sMTL1 formula in NNF at a linear blow-up only (Thm. 7 and Lemma 10). This can in turn be translated into an equivalent NSA (Lemmas 17 and 18) of exponential size in (Lemma 15). Language equivalence entails particularly that its language is non-empty iff is satisfiable. Non-emptiness for NSA can be decided in NLogSpace (Thm. 4) which is NPSpace measured in the size of . Savitch’s Theorem [15] then gives a PSpace upper bound.
5 Conclusion
We have investigated the expressiveness and computational complexity of MTL1, a variant of Metric Linear-Time Temporal logic MTL in wich the metric parameters do not constrain the occurrence of some event but their first occurrence (in an Until formula). The resulting logic is still exponentially more succinct than LTL. Unlike full MTL whose satisfiability problem is ExpSpace-complete, we obtained a PSpace upper bound for MTL1 by the construction of equivalent Streett automata of exponential size.
The main motivation for the study of this logic is given by links to State-Space Models in machine learning. Further work will elaborate on the connections between these formalisms. On the side of temporal logics, there is obvious further work in terms generalisations of the strict first-time semantics to a strict -th time semantics, constraining further moments in which an Until-formula gets satisfied. We suspect that for every fixed , the resulting logic MTLn remains PSpace-complete.
There are also obvious connections to Counting LTL [11], a variant of LTL with a counting operator. The first-time semantics is clearly expressible using counting operators by stating that the number of positions beforehand is zero. The relative succinctness between the two formalisms remains to be investigated, as is the case for MTL and MTL1.
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