1. Introduction
Many classic questions in formal methods can be seen as involving comparisons between different system runs or inputs. Consider the problem of verifying if a system satisfies a lineartime temporal property . Traditionally, this problem is phrased languagetheoretically: and are interpreted as sets of (infinite) words, and is determined to satisfy if . The problem, however, can also be framed in terms of a comparison between words in and . Suppose a word is assigned a weight of 1 if it belongs to the language of the system or property, and 0 otherwise. Then determining if amounts to checking whether the weight of every word in is less than or equal to its weight in [5].
The need for such a formulation is clearer in quantitative systems, in which every run of a word is associated with a sequence of (rationalvalued) weights. The weight of a run is given by aggregate function , which returns the realvalued aggregate value of the run’s weight sequence. The weight of a word is given by the supremum or infimum of the weight of all its runs. Common examples of aggregate functions include discountedsum and limitaverage.
In a wellstudied class of problems involving quantitative systems, the objective is to check if the aggregate value of words of a system exceed a constant threshold value [15, 16, 17]
. This is a natural generalization of emptiness problems in qualitative systems. Known solutions to the problem involve arithmetic reasoning via linear programming and graph algorithms such as negativeweight cycle detection, computation of maximum weight of cycles etc
[4, 19].A more general notion of comparison relates aggregate values of two weight sequences. Such a notion arises in the quantitative inclusion problem for weighted automata [1], where the goal is to determine whether the weight of words in one weighted automaton is less than that in another. Here it is necessary to compare the aggregate value along runs between the two automata. Approaches based on arithmetic reasoning do not, however, generalize to solving such problems. In fact, the known solution to discountedsum inclusion with integer discountfactor combines linear programming with a specialized subsetconstructionbased determinization step, rendering an EXPTIME algorithm [4, 7]. Yet, this approach does not match the PSPACE lower bound for discountedsum inclusion.
In this paper, we present an automatatheoretic formulation of this form of comparison between weighted sequences. Specifically, we introduce comparator automata (comparators, in short), a class of automata that read pairs of infinite weight sequences synchronously, and compare their aggregate values in an online manner. While comparisons between weight sequences happen implicitly in prior approaches to quantitative systems, comparator automata make these comparisons explicit. We show that this has many benefits, including generic algorithms for a large class of quantitative reasoning problems, as well as a direct solution to the problem of discountedsum inclusion that also closes its complexity gap.
A comparator for aggregate function for relation is an automaton that accepts a pair of sequences of bounded rational numbers iff , where is an inequality relation (, , , , ) or the equality relation . A comparator could be finitestate or (pushdown) infinitestate. This paper studies such comparators.
A comparator is regular if it is finitestate and accepts by the Büchi condition. We relate regular comparators to regular aggregate functions [13], and show that regular aggregatefunctions entail regular comparators. However, the other direction is still open: Does an regular comparator for an aggregate function and a relation imply that the aggregate function is also regular? Furthermore, we show that regular comparators lead to generic algorithms for a number of wellstudied problems including the quantitative inclusion problem, and in showing existence of winning strategies in incompleteinformation quantitative games. Our algorithm yields PSPACEcompleteness of quantitative inclusion when the regular comparator is provided. The same algorithm extends to obtaining finitestate representations of counterexample words in inclusion.
Next, we show that the discountedsum aggregation function admits an regular comparator for all relations iff the discountfactor is an integer. We use this result to prove that discountedsum aggregate function for discountfactor is regular iff is an integer. Furthermore, we use properties of regular comparators to conclude that the discountedsum inclusion is PSPACEcomplete, hence resolving the complexity gap.
Finally, we investigate the limitaverage comparator. Since limitaverage is only defined for sequences in which the average of prefixes converge, limitaverage comparison is not welldefined. We show that even a Büchi pushdown automaton cannot separate sequences for which limitaverage exists from those for which it does not. Hence, we introduce the novel notion of prefixaverage comparison as a relaxation of limitaverage comparison. We show that the prefixaverage comparator admits a comparator that is contextfree, i.e., given by a Büchi pushdown automaton, and we discuss the utility of this characterization.
This paper is organized as follows: Preliminaries are given in § 2. Comparator automata is formally defined in § 3. The connections between regular aggregate functions and regular comparators is discussed in Section 3.1. Generic algorithms for regular comparators are discussed in § 3.23.3. § 4 discusses discountedsum aggregate function and its comparators with noninteger rational discountfactors (§ 4.1) and integer discountfactors (§ 4.2). The construction and properties of prefixaverage comparator are given in § 5, respectively. We conclude with future directions in § 6.
1.1. Related work
The notion of comparison has been widely studied in quantitative settings. Here we mention only a few of them. Such aggregatefunction based notions appear in weighted automata [1, 18], quantitative games including meanpayoff and energy games [17], discountedpayoff games [3, 4], in systems regulating cost, memory consumption, power consumption, verification of quantitative temporal properties [15, 16], and others. Common solution approaches include graph algorithms such as weight of cycles or presence of cycle [19], linearprogrammingbased approaches, fixedpointbased approaches [9], and the like. The choice of approach for a problem typically depends on the underlying aggregate function. In contrast, in this work we present an automatatheoretic approach that unifies solution approaches to problems on different aggregate functions. We identify a class of aggregate functions, ones that have an regular comparator, and present generic algorithms for some of these problems.
2. Preliminaries
[Büchi automaton [21]]
A (finitestate) Büchi automaton is a tuple , , , , , where is a finite set of states, is a finite input alphabet, is the transition relation, is the set of initial states, and is the set of accepting states [21] . A Büchi automaton is deterministic if for all states and inputs , and . Otherwise, it is nondeterministic. A Büchi automaton is complete if for all states and inputs , . For a word , a run of is a sequence of states s.t. , and for all . Let denote the set of states that occur infinitely often in run . A run is an accepting run if . A word is an accepting word if it has an accepting run. Büchi automata are closed under settheoretic union, intersection, and complementation [21]. Languages accepted by these automata are called regular languages.
Reals over words [13]
Given an integer base , its digit set is . Let , then there exist unique words and such that . Thus, and are respectively the th least significant digit in the base representation of the integer part of , and the th most significant digit in the base representation of the fractional part of . Then, a realnumber in base is represented by , where if , if , and is the interleaved word of and . Clearly, . For all integer , we denote the alphabet of representation of realnumbers in base by . We adopt the definitions of function automata and regular functions [13] w.r.t. aggregate functions as follows: [Aggregate function automaton, Regular aggregate function] Let be a finite set, and be an integervalued base. A Büchi automaton over alphabet is an aggregate function automata of type if the following conditions hold:

For all , there exists at most one such that , and

For all , there exists an such that
and are the input and output alphabets, respectively. An aggregate function is regular under integer base if there exists an aggregate function automaton over alphabet such that for all sequences and , iff .
[Weighted automaton [11, 20]] A weighted automaton over infinite words is a tuple , where is a Büchi automaton with all states as accepting, is a weight function, and is the aggregate function [11, 20]. Words and runs in weighted automata are defined as they are in Büchi automata. The weightsequence of run of word is given by where for all . The weight of a run , denoted by , is given by . Here the weight of a word in weighted automata is defined as is a run of in . In general, weight of a word can also be defined as the infimum of the weight of all its runs. By convention, if a word its weight .
[Quantitative inclusion] Let and be weighted automata with the same aggregate function . The strict quantitative inclusion problem, denoted by , asks whether for all words , . The nonstrict quantitative inclusion problem, denoted by , asks whether for all words , .
Quantitative inclusion, strict and nonstrict, is PSPACEcomplete for limsup and liminf [11], and undecidable for limitaverage [17]. For discountedsum with integer discountfactor it is in EXPTIME [7, 11], and decidability is unknown for rational discountfactors
[Incompleteinformation quantitative games] An incompleteinformation quantitative game is a tuple , where , , are sets of states, observations, and actions, respectively, is the initial state, is the transition relation, is the weight function, and is the aggregate function. The transition relation is complete, i.e., for all states and actions , there exists a state s.t. . A play is a sequence , where . The observation of state is denoted by . The observed play of is the sequence , where . Player has incomplete information about the game ; it only perceives the observation play . Player receives full information and witnesses play . Plays begin in the initial state . For , Player selects action . Next, player selects the state , such that . The weight of state is the pair of payoffs . The weight sequence of player along is given by , and its payoff from is given by for aggregate function , denoted by , for simplicity. A play on which a player receives a greater payoff is said to be a winning play for the player. A strategy for player is given by a function since it only sees observations. Player follows strategy if for all , . A strategy is said to be a winning strategy for player if all plays following are winning plays for .
[Büchi pushdown automaton [14]] A Büchi pushdown automaton (Büchi PDA) is a tuple , where , , , and are finite sets of states, input alphabet, pushdown alphabet and accepting states, respectively. is the transition relation, is a set of initial states, is the start symbol. A run on a word of a Büchi PDA is a sequence of configurations satisfying (1) , , and (2) ( for all . Büchi PDA consists of a stack, elements of which are the tokens , and initial element . Transitions push or pop token(s) to/from the top of the stack. Let be the set of states that occur infinitely often in state sequence of run . A run is an accepting run in Büchi PDA if . A word is an accepting word if it has an accepting run. Languages accepted by Büchi PDA are called contextfree languages (CFL).
Notation
For an infinite sequence , denotes its th element, and denotes the finite word . Abusing notation, we write and if and are an accepting word and an accepting run of respectively. An infinite weightsequence is bounded if the absolute value of all of its elements are bounded by a fixed number.
For missing proofs and constructions, refer to the supplementary material.
3. Comparator automata
Comparator automata (often abbreviated as comparators) are a class of automata that can read pairs of weight sequences synchronously and establish an equality or inequality relationship between these sequences. Formally, we define: [Comparator automata] Let be a finite set of rational numbers, and denote an aggregate function. A comparator automaton for aggregate function with inequality or equality relation is an automaton over the alphabet that accepts a pair of (infinite) weight sequences iff
. From now on, unless mentioned otherwise, we assume that all weight sequences are bounded, naturalnumber sequences. The boundedness assumption is justified since the set of weights forming the alphabet of a comparator is bounded. For all aggregate functions considered in this paper, the result of comparison of weight sequences is preserved by a uniform linear transformation that converts rationalvalued weights into natural numbers; justifying the natural number assumption.
When the comparator for an aggregate function and a relation is a Büchi automaton, we call it an regular comparator. Likewise, when the comparator is a Büchi pushdown automaton, we call it an contextfree comparator. Due to closure properties of Büchi automata, if the comparator for an aggregate function for any one inequality is regular for all equality and inequality relations, then the comparator for the function for all inequality and equality relations also regular. Later, we see that discountedsum comparator is regular (§ 4) and prefixaverage comparator with (or ) is contextfree (§ 5).
Limsup comparator
We explain comparators through an example. The limit supremum (limsup, in short) of a bounded, integer sequence , denoted by , is the largest integer that appears infinitely often in . The limsup comparator for relation is a Büchi automaton that accepts the pair of sequences iff .
The working of the limsup comparator for relation is based on nondeterministically guessing the limsup of sequences and , and then verifying that . Büchi automaton (Fig. 1) illustrates the basic building block of the limsup comparator for relation . Automaton accepts pair of number sequences iff , and , for integer . (Lemma 3).
Let and be nonnegative integer sequences bounded by . Büchi automaton (Fig. 1) accepts iff , and .
Proof.
Let have an accepting run in . We show that . The accepting run visits state infinitely often. Note that all incoming transitions to accepting state occur on alphabet while all transitions between states and occur on alphabet , where denotes the set . So, the integer must appear infinitely often in and all elements occurring infinitely often in and are less than or equal to . Therefore, if is accepted by then , and , and .
Conversely, let . We prove that is accepted by . For an integer sequence when integers greater than can occur only a finite number of times in . Let denote the index of the last occurrence of an integer greater than in . Similarly, since , let be index of the last occurrence of an integer greater than . Therefore, for sequences and integers greater than will not occur beyond index . Büchi automaton (Fig. 1) nondeterministically determines . On reading the th element of input word , the run of exits the start state and shifts to accepting state . Note that all runs beginning at state occur on alphabet where . Therefore, can continue its infinite run even after transitioning to . To ensure that this is an accepting run, the run must visit accepting state infinitely often. But this must be the case, since occurs infinitely often in , and all transitions on , for all , transition into state . Hence, for all integer sequences , bounded by , if , and , the automaton accepts . ∎
Let be an integer upper bound, and be the inequality relation. The limsup comparator with relation accepting pair of boundedsequence iff is regular.
Proof.
Due to closure properties of Büchi automata, this implies that limsup comparator for all inequalities and equality relation is also regular. The limit infimum (liminf, in short) of an integer sequence is the smallest integer that appears infinitely often in it; its comparator has a similar construction to the limsup comparator. One can further prove that the limsup and liminf aggregate functions are also regular aggregate functions.
3.1. Regular aggregate functions
This section draws out the relationship between regular aggregate functions and regular comparators. We begin with showing that regular aggregate functions entails regular comaparators for the aggregate function. Let be the upperbound on weight sequences, and be the integer base. Let be an aggregate function. If aggregate function is regular under base , then its comparator for all inequality and equality relations is also regular.
Proof.
We show that if an aggregate function is regular under base , then its comparator for relation is regular. By closure properties of regular comparators, this implies that comparators of the aggregate function are regular for all inequality and equality relations.
But first we prove that for a given integer base there exists an automaton such that for all , accepts iff . Let , and be an integer base. Let and . Then, the following statements can be proven using simple evaluation from definitions:

When and . Then .

When

If : Since and eventually only see digit i.e. they are necessarily identical eventually, there exists an index such that it is the last position where and differ. If , then . If , then .

If but : Let be the first index where and differ. If then . If then .

Finally, if and : Then .


When

If : Since and eventually only see digit i.e. they are necessarily identical eventually. Therefore, there exists an index such that it is the last position where and differ. If , then . If , then .

If but : Let be the first index where and differ. If then . If then .

Finally, if and : Then .


When and . Then .
Since the conditions given above are exhaustive and mutually exclusive, we conclude that for all and integer base , let and . Then iff one of the following conditions occurs:

and .

, , and when is the last index where and differ.

, , , and when is the first index where and differ.

, , and when is the last index where and differ.

, , , and when is the first index where and differ.
Note that each of these five condition can be easily expressed by a Büchi automaton over alphabet for an integer . For an integer , the union of all these Büchi automata will result in a Büchi automaton such that for all and and , iff interleaved word .
Now we come to the main part of the proof. Let be an regular aggregate function with aggregate function automata . We will construct an regular comparator for with relation . Note that is present in the comparator iff for and , for as described above. Since and are both Büchi automata, the comparator for function with relation is also a Büchi auotmaton. Therefore, the comparator for aggregate function with relation is regular. ∎
The converse direction of whether regular comparator for an aggregate function for all inequality or equality relations will entail regular functions under an integer base is trickier. For all aggregate functions considered in this paper, we see that whenever the comparator is regular, the aggregate function is regular as well. However, the proofs for this have been done on a casebycass basis, and we do not have an algorithmic procedure to derive a function (Büchi) automaton from its regular comparator. We also do not have an example of an aggregate function for which the comparator is regular but the function is not. Therefore, we arrive at the following conjecture: Let be the upperbound on weight sequences, and be the integer base. Let be an aggregate function. If the comparator for an aggregate function is regular for all inequality and equality relations, then its aggregate function is also regular under base .
3.2. Quantitative inclusion
The aggregate function or comparator of a quantitative inclusion problem refer to the aggregate function or comparator of the associated aggregate function. This section presents a generic algorithm (Algorithm 1) to solve quantitative inlcusion between weighted automata and with comparators. This section focusses on the nonstrict quantitative inclusion. (Algorithm 1) is an algorithm for quantitative inclusion between weighted automata and with regular comparator for relation . takes , and as input, and returns iff . The results for strict quantitative inclusion are similar. We use the following motivating example to explain steps of Algorithm 1.
Motivating example
Let weighted automata and be as illustrated in Fig. 33 with the limsup aggregate function. The word has one run with weight sequence in and two runs with weight sequence and run with weight sequence . Clearly, ). Therefore . From Theorem 3 we know that the limsup comparator for is regular.
We use Algorithm 1 to show that using its regular comparator for . Intuitively, the algorithm must be able to identify that for run of in , there exists a run in s.t. is accepted by the limsup comparator for .
Key ideas
A run in on word is said to be dominated w.r.t if there exists a run in on the same word such that . holds if for every run in is dominated w.r.t. .
constructs Büchi automaton that consists of exactly the domianted runs of w.r.t . returns iff contains all runs of . To obtain , it constructs Büchi automaton that accepts word iff and are runs of the same word in and respectively, and i.e. if and are weight sequence of and , respectively, then is present in the regular comparator for aggregate function with relation . The projection of on runs of results in .
Algorithm details
For sake a simplicity, we assume that every word present in is also present in i.e. (qualitative inclusion). has three steps: (a). (Lines 34): Enables unique identification of runs in and through labels. (b). (Lines 57): Compares weight of runs in with weight of runs in , and constructs . (c). (Line 8): Ensures if all runs of are diminished.

: transforms weighted automaton into Büchi automaton by converting transition with weight in to transition in , where is a unique label assigned to transition . The word iff run on word with weight sequence . Labels ensure bijection between runs in and words in . Words of have a single run in . Hence, transformation of weighted automata and to Büchi automata and enables disambiguation between runs of and (Line 34).

: The output of this step is the Büchi automaton , that contains the word iff is a dominated run in w.r.t (Lines 57).
constructs s.t. word iff and are runs of the same word in and respectively (Line 5). Concretely, for transition in automaton , where , transition is in , as shown in Figure 6.

: iff (qualitative equivalence) since consists of all runs of and consists of all domianted runs w.r.t (Line 8).
Büchi automaton consists of all domianted runs in w.r.t .
Proof.
Let be the comparator for
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