Abstract 1 Introduction 2 Preliminaries 3 First properties and examples 4 Polynomial-time minimisation of HD generalised coBüchi automata 5 NP-completeness of minimisation of deterministic and HD generalised Büchi automata 6 Conclusion References

On the Minimisation of Deterministic and History-Deterministic Generalised (Co)Büchi Automata

Antonio Casares ORCID University of Warsaw, Poland Olivier Idir IRIF, Université Paris-Cité, France Denis Kuperberg ORCID LIP, CNRS, ENS Lyon, France Corto Mascle ORCID LaBRI, Université de Bordeaux, France
Max Planck Institute for Software Systems (MPI-SWS), Kaiserslautern, Germany
Aditya Prakash ORCID University of Warwick, UK
Abstract

We present a polynomial-time algorithm minimising the number of states of history-deterministic generalised coBüchi automata, building on the work of Abu Radi and Kupferman on coBüchi automata. On the other hand, we establish that the minimisation problem for both deterministic and history-deterministic generalised Büchi automata is NP-complete, as well as the problem of minimising at the same time the number of states and colours of history-deterministic generalised coBüchi automata.

Keywords and phrases:
Automata minimisation, omega-regular languages, good-for-games automata
Funding:
Antonio Casares: Supported by the Polish National Science Centre (NCN) grant “Polynomial finite state computation” (2022/46/A/ST6/00072).
Copyright and License:
[Uncaptioned image] © Antonio Casares, Olivier Idir, Denis Kuperberg, Corto Mascle, and Aditya Prakash; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Theory of computation Verification by model checking
Related Version:
Long version with appendices: https://arxiv.org/abs/2407.18090
Editors:
Jörg Endrullis and Sylvain Schmitz

This document contains hyperlinks. On an electronic device, the reader can click on words or symbols (or just hover over them on some PDF readers) to see their definition.

1 Introduction

First introduced by Büchi to obtain the decidability of monadic second order logic over (,𝗌𝗎𝖼𝖼) [14], automata over infinite words (also called ω-automata) have become a well-established area of study in Theoretical Computer Science. Part of its success is due to its applications to model checking (verify whether a system satisfies some given specifications) [5, 42, 24] and synthesis (given a set of specifications, automatically construct a system satisfying them) [13, 35]. In many of these applications, mainly in problems related to synthesis, non-deterministic models of automata are not well-suited, and costly determinisation procedures are usually needed [38].

In 2006, Henzinger and Piterman [26] proposed111Similar ideas had been previously investigated by Kupferman, Safra and Vardi [31], and Colcombet studied history-determinism in the context of cost functions [20]. a model of automata, called history-deterministic (HD)222These automata were first introduced under the name good-for-games (GFG). Currently, these two notions are no longer used interchangeably, although they coincide in the case of ω-automata. We refer to the survey [11] for further discussions., presenting a restricted amount of non-determinism so that they exactly satisfy the properties that are needed for applications in synthesis. Namely, these automata do not need to guess the future: an automaton is history-deterministic if it admits a strategy resolving the non-determinism on the fly, in such a way that the run built by the strategy is accepting whenever the input word belongs to the language of the automaton. Since their introduction, several lines of research have focused on questions such as the succinctness of history-deterministic automata [30, 18], the problem of recognising them [4, 8], or extensions to other settings [32, 9, 10].

Minimisation of automata stands as one of the most fundamental problems in automata theory, for various reasons. Firstly, for its applications: when employing algorithms that rely on automata, having the smallest possible ones is crucial for efficiency. Secondly, beneath the problem of minimisation lies a profoundly fundamental question: What is the essential information needed to represent a formal language? A cornerstone result about automata over finite words is that each regular language admits a unique minimal deterministic automaton, in which states corresponds to the residuals of the language (the equivalence classes of the Myhill-Nerode congruence). Moreover, this minimal automaton can be obtained from an equivalent deterministic automaton with n states in time 𝒪(nlogn) [27].

However, the situation is quite different in the case of ω-automata. Contrary to the case of finite words, the residuals of a language are not sufficient to construct a correct deterministic automaton in general. In 2010, Schewe proved that the minimisation of deterministic Büchi automata is 𝖭𝖯-complete [39]. That appeared to be a conclusion to the minimisation problem, but a crucial aspect of his proof was that the 𝖭𝖯-completeness is established for automata with the acceptance condition over states, and this proof does not generalise to transition-based automata. A surprising positive result was obtained in 2019 by Abu Radi and Kupferman: we can minimise history-deterministic coBüchi automata using transition-based acceptance in polynomial time [1]. One year later, Schewe showed that the very same problem becomes 𝖭𝖯-complete if state-based acceptance is used [40]. Multiple other results have backed the idea that transition-based acceptance is a better-suited model; we refer to [16, Chapter VI] for a detailed discussion. The work of Abu Radi and Kupferman raised the question of what is the complexity of the minimisation problem for other classes of transition-based automata such as (history-)deterministic Büchi automata. Since then, to the best of our knowledge, the only further result concerning minimisation of transition-based automata is Casares’ 𝖭𝖯-completeness proof for the problem of minimising deterministic Rabin automata [15].

In this paper, we focus our attention on generalised Büchi and generalised coBüchi automata, in which the acceptance condition is given, respectively, by conjunctions of clauses “see colour c infinitely often”, and by disjunctions of “eventually avoid colour d”. Generalised (co)Büchi automata are as expressive as (co)Büchi automata, but they can be more succinct, due to their more complex acceptance condition. These automata appear naturally in the model-checking and synthesis of temporal properties [21, 25, 41]; for instance, SPOT’s LTL-synthesis tool transforms a given LTL formula into a generalised Büchi automaton [22, 33]. Also, many efficient algorithms for their emptiness check have been developed [36, 37, 6].

Several works have approached the problem of reducing the state-space of generalised Büchi automata, which is usually done either by the use of simulations [41, 29] (which do not yield minimal automata), or by the application of SAT solvers [23, 3]. However, to the best of our knowledge, no theoretical result about the exact complexity of this minimisation problem appears in the literature.

Contributions

We provide a polynomial-time minimisation algorithm for history-deterministic generalised coBüchi automata (Theorem 11). Our algorithm uses Abu Radi-Kupferman’s minimal history-deterministic coBüchi automaton as a starting point, and reduces the state-space of this automaton in an optimal way to use a generalised coBüchi condition.

We prove that the minimisation problem is 𝖭𝖯-complete for history-deterministic generalised Büchi automata (Theorem 28), as well as for deterministic generalised Büchi and generalised coBüchi automata (Theorem 29). We remark that both the 𝖭𝖯-hardness and the 𝖭𝖯-upper bound are challenging. Indeed, to obtain that the problem is in 𝖭𝖯, we first need to prove that a minimal HD generalised Büchi automaton only uses a polynomial number of output colours. Additionally, we adapt a proof from [19] to show that minimising at the same time the number of states and colours is 𝖭𝖯-complete for all the previous models, including history-deterministic generalised coBüchi automata (Theorem 30).

We summarise the results about the state-minimisation of transition-based automata in Table 1.

Table 1: Complexity of the minimisation problem for different types of transition-based automata.

We note that the 𝖯𝖳𝖨𝖬𝖤 complexity of recognising HD automata can be lifted from Büchi and coBüchi conditions to their generalised versions (Corollary 10). This result can be considered folklore, although we have not find it explicitly in the literature. In the long version, we also lift the characterisation based on the G2 game from (co)Büchi automata to generalised ones (a similar remark was suggested in the conclusion of [8]).

State-minimality.

In this paper, we primarily focus our attention on the minimisation of the number of states of the automata. In Theorem 30 we also consider the minimisation of both the number of states and colours of the acceptance condition. We highlight that the decision on how we measure the size of the automata is orthogonal to putting the acceptance condition over transitions.

The reader may wonder why we focus on these quantities and not, e.g., on the number of transitions. This choice, which is standard in the literature ([2, 39]), is justified by various reasons. First, the number of transitions of an automaton is polynomial in the number of states. Indeed, we can assume that there are no two transitions between two states over the same input letter (see [18, Prop.18]), therefore, |Δ||Q|2|Σ|. Maybe more importantly, in the case of automata over finite words, each state of the minimal automaton carry a precise information about the language it recognises: a residual of it. Ideally, a construction for a state-minimal automaton for an ω-regular language should lead to an understanding of the essential information necessary to represent it.

The interest of minimising both the number of states and the number of colours comes from the fact that the number of colours can be exponential on the number of states, but the size of the representation of the automaton is polynomial in the sum of these quantities.

2 Preliminaries

The disjoint union of two sets A,B is written AB. The empty word is denoted ε. A factor of a word w is a word u such that there exist words x,y with w=xuy. For an infinite word wSSω, we denote 𝖨𝗇𝖿(w) the set of letters occurring infinitely often in w.

2.1 Automata

We let Σ be a finite alphabet. An automaton is a tuple 𝒜=(Q,SS,qinit,Δ,Γ,𝖼𝗈𝗅,W), where Q is its set of states, qinit its initial state, ΔQ×Σ×Q its set of transitions, Γ its output alphabet, 𝖼𝗈𝗅:ΔΓ a labelling with colours, and WΓω its acceptance condition. A state q is called reachable if there exists a path from qinit to q. The size of an automaton is its number of states, written |Q|. We write pa:cq if (p,a,q)Δ and 𝖼𝗈𝗅((p,a,q))=c.

A run ρ on an infinite word w=a1a2Σω is an infinite sequence of transitions ρ=(q0,a1,q1)(q1,a2,q2)(q2,a3,q3),Δω with q0=qinit. It is accepting if the infinite word c1c2Γω defined by ci=𝖼𝗈𝗅(qi1,ai,qi), called the output of ρ, belongs to W.

The language of an automaton 𝒜, denoted (𝒜), is the set of words that admit an accepting run. We say that two automata 𝒜 and over the same alphabet are equivalent if (𝒜)=().

An automaton 𝒜 is deterministic (resp. complete) if, for all (p,a)Q×SS, there exists at most (resp. at least) one qQ such that (p,a,q)Δ. We note that if 𝒜 is deterministic, a word wSSω admits at most one run in 𝒜.

2.2 Acceptance conditions

In this paper we will focus on automata using generalised Büchi and generalised coBüchi acceptance conditions. A generalised Büchi condition can be seen as a conjunction of Büchi conditions, while a generalised coBüchi condition can be seen as a disjunction of coBüchi conditions.

A generalised Büchi condition with k colours is defined over the output alphabet Γ=2C, with C a set of k output colours, as

𝗀𝖾𝗇𝖡C={wΓω𝖨𝗇𝖿(w)=C}.

It contains sequences of sets of colours such that every colour is seen infinitely often. Usually, we take C=[k]={1,2,,k}.

The dual condition is the generalised coBüchi condition with k colours. That is, we define:

𝗀𝖾𝗇𝖢𝗈𝖡C={wΓω𝖨𝗇𝖿(w)C}.

It contains sequences of sets of colours such that at least one colour is seen finitely often.

The size of the representation of an automaton using a generalised (co)Büchi condition with k colours is |Q|+|SS|+k; such an automaton can be described in polynomial space in this measure.

A Büchi condition (resp. coBüchi condition) can be defined as a generalised Büchi (resp. generalised coBüchi) condition in which k=1. In this case, we call Büchi transitions (resp. coBüchi transitions) the transitions (p,a,q)Δ such that 𝖼𝗈𝗅((p,a,q))={1}. An automaton using an acceptance condition of type X is called an X-automaton.

A language LSSω is (co)Büchi recognisable if there exists a deterministic (co)Büchi automaton 𝒜 such that 𝒜 recognises L. These coincide with languages recognised by generalised (co)Büchi automata (see Corollary 9). We note that non-deterministic (generalised) Büchi automata are strictly more expressive, while non-deterministic (generalised) coBüchi automata are as expressive as deterministic ones [34].

2.3 History-determinism

An automaton is called history-deterministic (or HD for short), if there exists a function, called a resolver, that resolves the non-determinism of 𝒜 depending only on the prefix of the input word read so far. Formally, a resolver for an automaton 𝒜 is a function σ:Σ+Δ such that for all words w=a0a1SSω, the sequence σ(w)=σ(a0)σ(a0a1)σ(a0a1a2)Δω (called the run induced by σ over w) satisfies:

  1. 1.

    σ(w) is a run on w in 𝒜,

  2. 2.

    if w(𝒜), then σ(w) is an accepting run.

An automaton is history-deterministic if it admits a resolver. We say that a (deterministic/history-deterministic) automaton is minimal if it has a minimal number of states amongst equivalent (deterministic/history-deterministic) automata.

 Remark 1.

Every deterministic automaton is HD. While the converse is false (see Example 2 below), we note that any language LSSω recognised by an HD Büchi automaton (resp. coBüchi automaton), can be recognised by a deterministic Büchi automaton (resp. deterministic coBüchi automaton[31].

Example 2 (From [17, Ex. 2.3]).

Let SS={a,b,c} and L={wSSω{b,c}𝖨𝗇𝖿(w)}, that is, L is the set of words that contain either b or c only finitely often.

In Figure 1 we show an automaton recognising L that is not determinisable by prunning, that is, it cannot be made deterministic just by removing transitions.

We claim that this automaton is history-deterministic. First, we remark that the only non-deterministic choice appears when reading letter a from the state q1. A resolver can be defined as follows: whenever we have arrived at q1 from q0 (by reading letter c), if we are given letter a we go to state q2; if we have arrived at q1 from q2 (by reading letter b), we will go to state q0. Therefore, if after some point letter b (resp. letter c) does not appear, we will stay forever in state q2 (resp. state q1) and accept.

Figure 1: A history-deterministic coBüchi automaton recognising the language L={wSSω{b,c}𝖨𝗇𝖿(w)}. CoBüchi transitions are represented with a dot on them.

2.4 Residuals and prefix-independence

Let LSSω and uSS. The residual of L with respect to u is the language

u1L={wSSωuwL}.

We write [u]L={vSSu1L=v1L}, and 𝖱𝖾𝗌(L) for the set of residuals of a language L.

Given an automaton 𝒜 and a state q, we denote 𝒜q the automaton obtained by setting q as initial state, and we refer to (𝒜q) as the language recognised by q. We say that two states q,p are equivalent, written qp, if they recognise the same language. We note [q]𝒜 the set of states equivalent to q (we simply write [q] when 𝒜 is clear from the context).

We say that an automaton 𝒜 is semantically deterministic if non-deterministic choices lead to equivalent states, that is, if for every state q and pair of transitions q𝑎p1, q𝑎p2 we have p1p2.

If 𝒜 is semantically deterministic and uSS is a word labelling a path from the initial state to q, then (𝒜q)=u1L. We say then that u1L is the residual associated to q. For a residual R𝖱𝖾𝗌(L) we denote QR the set of states of 𝒜 recognising R. We remark that QR=[q]𝒜 for any state q recognising R.

We say that L is prefix-independent if for all wSSω and uSS, wLuwL.

 Remark 3.

A language L is prefix-independent if and only if it has a single residual.

2.5 Morphisms of automaton structures

An automaton structure over an alphabet SS is a tuple 𝒮=(Q,Δ), where ΔQ×SS×Q. Let 𝒮1=(Q1,Δ1) and 𝒮2=(Q2,Δ2) be two automaton structures over the same alphabet. A morphism of automaton structures is a mappings ϕ:Q1Q2 such that for every (q,a,q)Δ1, (ϕ(q),a,ϕ(q))Δ2. We note that such a morphism induces a function ϕΔ:Δ1Δ2 sending (q,a,q) to (ϕ(q),a,ϕ(q)). We also denote this function ϕ, whenever no confusion arises, and denote a morphism of automaton structures by ϕ:𝒮1𝒮2.

3 First properties and examples

We discuss a further example of a history-deterministic automaton and state some well-known facts about these automata that will be relevant for the rest of the paper.

3.1 A central example

The following automata will be used as a running example in Section 4.

Example 4.

Let SSn be an alphabet of size n, and let

Ln={wSSnω for some xSSn the factor xx appears only finitely often in w}.

On the left of Figure 2 we show a history-deterministic generalised coBüchi automaton recognising Ln with just 2 states (we show it for SS3={a,b,c}, but the construction clearly generalises to any n). The set of colours is C={1,2,3}, and we accept if eventually some colour is not produced. A resolver can be defined as follows: in a round-robin fashion, we bet that the factor that does not appear is aa, then bb, then cc. While factor aa is not seen, we will take transition q0𝑎q1 whenever letter a is read, to try to avoid colour 1. Whenever factor aa is read, we switch to the corresponding strategy with letter b, trying to avoid colour 2. If eventually factor xx is not produced, for x{a,b,c}, then some colour will forever be avoided.

We show a deterministic coBüchi automaton for L3 on the right of Figure 2. Applying the characterisation of Abu Radi and Kupferman [2] (see Lemma 15), we can prove that this automaton is minimal amongst HD coBüchi automata. More generally, we can prove that a minimal HD coBüchi automaton for Ln has at least 2n states , and in fact, in this case, this optimal bound can be achieved with a deterministic automaton.

Figure 2: On the left, a history-deterministic generalised coBüchi automaton recognising the language L3 of words eventually avoiding factor xx for some letter x. On the right, a minimal deterministic coBüchi automaton for the same language (coBüchi transitions have a dot on them). In both cases, the initial state is irrelevant, as the language is prefix-independent.

3.2 Duality Büchi - coBüchi

 Remark 5.

Let 𝒜 be a deterministic generalised Büchi automaton of size n and using k output colours. It suffices to replace the acceptance condition 𝗀𝖾𝗇𝖡[k] with 𝗀𝖾𝗇𝖢𝗈𝖡[k] to obtain a deterministic generalised coBüchi automaton of size n and using k output colours recognising the complement language SSω(𝒜). Symmetrically, we can turn any deterministic generalised coBüchi automaton into a deterministic generalised Büchi automaton with the same number of states and colours recognising the complement language. As a consequence, the minimisations of deterministic generalised Büchi automaton and deterministic generalised coBüchi automaton are linear-time-equivalent problems.

We highlight that the hypothesis of determinism in the previous remark is crucial. This duality property no longer holds for non-deterministic (or history-deterministic) automata.

Lemma 6.

There exists a history-deterministic generalised coBüchi automaton 𝒜 such that any history-deterministic generalised Büchi automaton recognising SSω(𝒜) has strictly more states than 𝒜.

Such an example is provided by the language L3 from Example 4 (in the long version we prove that any non-deterministic generalised Büchi automaton recognising SSω(𝒜) has at least 3 states). Relatedly, for the non-generalised conditions, Kuperberg and Skrzypczak showed that the gap between an HD coBüchi and an HD Büchi automaton for the complement language can be exponential as well [30], using the link between complementation and determinisation of HD automata from [7, Thm 4].

3.3 From generalised (co)Büchi to (co)Büchi

The idea of this construction is to define a particular deterministic coBüchi automaton recognizing 𝗀𝖾𝗇𝖢𝗈𝖡C, and to associate it to the input generalised coBüchi automaton via a cascade composition (defined below) in order to obtain the wanted coBüchi automaton. We will now detail these different steps.

Deterministic coBüchi automaton for 𝗴𝗲𝗻𝗖𝗼𝗕𝑪.

Let C={1,2,,k} be a set of k colours; for convenience, in the context of colours, we will use the symbol + to denote addition modulo k, in particular, k+1=1. We build a deterministic coBüchi automaton 𝒟CcoB over the alphabet Γ=2C recognising the language 𝗀𝖾𝗇𝖢𝗈𝖡C. It has as a state qi for each colour iC and contains the transitions qiX:qi, if iX, and qiX:1qi+1, if iX, for all XΓ. The initial state is arbitrary.

We claim that the automaton 𝒟CcoB recognises the language 𝗀𝖾𝗇𝖢𝗈𝖡C. First, we remark that the accepting runs of 𝒟CcoB are exactly those that eventually remain forever in a state qi. Let w=w1w22C. If w is accepted by 𝒟CcoB, then the run on w eventually stays in a qi, so w eventually does not contain colour i, and w𝗀𝖾𝗇𝖢𝗈𝖡C. Conversely, if w is rejected by 𝒟CcoB, it takes all transitions qiX:1qi+1 infinitely often, so w must contain all colours in C infinitely often.

We define in a similar fashion a deterministic Büchi automaton 𝒟CB recognising the language 𝗀𝖾𝗇𝖡C, simply by changing the acceptance condition of 𝗀𝖾𝗇𝖢𝗈𝖡C to 𝗀𝖾𝗇𝖡C.

 Remark 7.

The automaton 𝒟CcoB has k states, but exponentially many transitions. This is made possible by the fact that its alphabet Γ is exponential in the number of colours k.

Cascade composition of automata.

Let 𝒜=(Q𝒜,SS𝒜,qinit𝒜,Δ𝒜,Γ𝒜,𝖼𝗈𝗅𝒜,W𝒜) and =(Q,SS,qinit,Δ,Γ,𝖼𝗈𝗅B,WB) be two automata such that SS=Γ𝒜 (i.e., is an automaton over the set of output colours of 𝒜). The cascade composition of 𝒜 and is the automaton over SS𝒜 defined as:

𝒜=(Q𝒜×Q,SS𝒜,(qinit𝒜,qinit),Δ,Γ,𝖼𝗈𝗅,W),

with transitions (p𝒜,p)a:c(q𝒜,q) if p𝒜a:bq𝒜Δ𝒜 and pb:cqΔ.

Intuitively, given a word in SS𝒜ω, we feed the output of 𝖼𝗈𝗅𝒜 directly as input to , while keeping track of the progression in both automata. We accept according to the acceptance condition of .

Lemma 8 (Folklore).

Let 𝒜 be an automaton with acceptance condition WΓω, and let be a deterministic automaton over Γ recognising W. Then 𝒜 recognises (𝒜), and the automaton 𝒜 is history-deterministic (resp. deterministic) if and only if 𝒜 is.

Thus, to convert a generalised coBüchi automaton 𝒜 to an equivalent coBüchi one, we can just compose it with 𝒟CcoB. The symmetric result holds for generalised Büchi automata.

Corollary 9 (Folklore).

Let 𝒜 be a generalised coBüchi automaton using C as output colours. The automaton 𝒟CcoB𝒜 is a coBüchi automaton equivalent to 𝒜 which is (history-)deterministic if and only if 𝒜 is. Moreover, 𝒟CcoB𝒜 can be computed in polynomial time in the size of the representation of 𝒜. The same is true for generalised Büchi automata.

We note that 𝒟CcoB𝒜 has k|𝒜| states, where k=|C|, but it might have exponentially many transitions in k. However, we underline that we can compute 𝒟CcoB𝒜 from 𝒜 in polynomial time in the size of its representation. Indeed, we just need to compose 𝒜 with the restriction of 𝒟CcoB to transitions whose letters are subsets of colours that appear in 𝒜.

Deciding history-determinism.

The problem of deciding whether an automaton is HD is known to be in 𝖯𝖳𝖨𝖬𝖤 for Büchi and coBüchi automata [30, 4, 8]. Combining this fact with Corollary 9, we directly obtain:

Corollary 10.

Given a generalised Büchi (resp. generalised coBüchi) automaton, it is in 𝖯𝖳𝖨𝖬𝖤 to decide whether it is history-deterministic.

A different proof of Corollary 10, which goes through the G2 game [4], is presented in the long version.

4 Polynomial-time minimisation of HD generalised coBüchi automata

In this section we present one of the main contributions of the paper (Theorem 11): history-deterministic generalised coBüchi automata can be minimised in polynomial time.

Theorem 11.

Given a history-deterministic generalised coBüchi automaton, we can build in polynomial time in its representation an equivalent history-deterministic generalised coBüchi automaton with a minimal number of states.

The proof of this result strongly relies on the construction of minimal coBüchi automata by Abu Radi and Kupferman [2]. We will show that, for a coBüchi recognisable language L, we can extract a minimal HD generalised coBüchi automaton for L from its minimal HD coBüchi automaton.

In Section 4.1 we introduce some terminology and state the main property satisfied by the minimal HD coBüchi automaton of Abu Radi and Kupferman. We then present our construction, decomposing it in two steps for simplicity: first we construct a minimal HD generalised coBüchi automaton in the case of prefix-independent languages in Section 4.2, and in Section 4.3, we show how to get rid of the prefix-independence assumption.

4.1 Minimisation of HD coBüchi automata

Safe components and safe languages.

A path q[Uncaptioned image]q in a coBüchi automaton is safe if no coBüchi transition appears on it. Let 𝒜𝗌𝖺𝖿𝖾 be the automaton obtained by removing from 𝒜 all coBüchi transitions. A safe component of 𝒜 is a strongly connected component (i.e., a maximal set of states which are all reachable from each other) of 𝒜𝗌𝖺𝖿𝖾; formally, this is an automaton structure 𝒮=(S,Δ𝒮) with SQ𝒜 and Δ𝒮Δ𝒜. We let 𝖲𝖺𝖿𝖾(𝒜) be the set of safe components of 𝒜.

We define the safe language of a state q as:

𝖲𝖺𝖿𝖾(𝒜q)={wSSω there is a run q[Uncaptioned image] in 𝒜𝗌𝖺𝖿𝖾}.
Example 12.

The safe components of the automaton on the right of Figure 2 (page 2) have as set of states: S1={q0,q1}, S2={p0,p1} and S3={t0,t1}. The safe language of q0 is 𝖲𝖺𝖿𝖾(𝒜q0)={wSSωw does not contain the factor aa}.

Nice coBüchi automata.

We say that a coBüchi automaton 𝒜 is in normal form if all transitions between two different safe components are coBüchi transitions. We note that any coBüchi automaton can be put in normal form without modifying its language by setting all transitions between two different safe components to be coBüchi. We say that 𝒜 is safe deterministic if 𝒜𝗌𝖺𝖿𝖾 is a deterministic automaton. That is, if the non-determinism of 𝒜 appears exclusively in coBüchi transitions. We say that 𝒜 is nice if all its states are reachable, it is semantically deterministic, in normal form, and safe deterministic.

It is not difficult to see that any history-deterministic automaton 𝒜 can be assumed to be semantically deterministic. This means that different choices made by a resolver from the same state with different histories must be consistent with the residual, i.e. must lead to states accepting the same language, which is the language u1L(𝒜) after reading a word u. Kuperberg and Skrzypczak showed the more involved result that we can moreover assume safe determinism [30]. All in all, we have:

Lemma 13 ([30]).

Every history-deterministic coBüchi automaton 𝒜 can be turned in polynomial time into an equivalent nice HD coBüchi automaton 𝒜nice such that:

  • |𝒜nice||𝒜|,

  • For every safe component 𝒮 of 𝒜nice, there is some safe component 𝒮 of 𝒜 with |𝒮||𝒮|.

Although the second item of the previous proposition is not explicitly stated in [30], it simply follows from the fact that all the transformations used to turn 𝒜 into a nice automaton either add coBüchi transitions to 𝒜 or remove transitions from it. These operations can only subdivide safe components.

Minimal HD coBüchi automata.

We present the necessary conditions for the minimality of history-deterministic coBüchi automata identified by Abu Radi and Kupferman [2].

We say that a coBüchi automaton 𝒜 is safe centralised if for all equivalent states qp, if the safe languages of q and p are comparable for the inclusion relation (𝖲𝖺𝖿𝖾(𝒜q)𝖲𝖺𝖿𝖾(𝒜p) or vice versa), then they are in the same safe component of 𝒜. It is safe minimal if for all states qp, the equality 𝖲𝖺𝖿𝖾(𝒜q)=𝖲𝖺𝖿𝖾(𝒜p) implies q=p.

Example 14.

The automaton on the right of Figure 2 is safe minimal and safe centralised. However, the automaton from Figure 1 is not safe centralised, as 𝖲𝖺𝖿𝖾(𝒜q1)=𝖲𝖺𝖿𝖾(𝒜q2), but q1 and q2 appear in different safe components.

Lemma 15 ([2, Lemma 3.5]).

Let 𝒜min be a nice, safe minimal and safe centralised HD coBüchi automaton. Then, for any equivalent nice HD coBüchi automaton 𝒜 there is an injection η:𝖲𝖺𝖿𝖾(𝒜min)𝖲𝖺𝖿𝖾(𝒜) such that for every safe component 𝒮𝖲𝖺𝖿𝖾(𝒜min), it holds that |𝒮||η(𝒮)|.

Minimality of such automata directly follows:

Corollary 16.

Let 𝒜min be a nice, safe minimal and safe centralised HD coBüchi automaton. Then, the number of states of 𝒜min is minimal among all HD coBüchi automata recognising the same language.

Theorem 17 ([2, Theorem 3.15]).

Any coBüchi recognisable language L can be recognised by a nice, safe minimal and safe centralised HD coBüchi automaton 𝒜L𝖼𝗈𝖡. Moreover, such an automaton 𝒜L𝖼𝗈𝖡 can be computed in polynomial time from any HD coBüchi automaton recognising L.

4.2 Minimal HD generalised coBüchi automata: prefix-independent case

In this subsection, we show how to minimise history-deterministic generalised coBüchi automata recognising prefix-independent languages. The prefix-independence hypothesis will be removed in the next subsection.

Let LSSω be a prefix-independent coBüchi recognisable language, and let 𝒜 be a history-deterministic generalised coBüchi automaton recognising it.

Combining Corollary 9 and Theorem 17, we obtain that we can build in polynomial time the minimal HD coBüchi automaton 𝒜L𝖼𝗈𝖡 for L. Let 𝖲𝖺𝖿𝖾(𝒜L𝖼𝗈𝖡)={𝒮1,,𝒮k} be an enumeration of the safe components of 𝒜L𝖼𝗈𝖡, with Si and Δi the sets of states and transitions of each safe component, respectively. We show how to build an HD generalised coBüchi automaton 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 of size nmax=max1ik|Si| and using k output colours.

Intuitively, 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 will be the full automaton (it contains transitions between all pairs of states, for all input letters). Since |Si|nmax, we can map each safe component 𝒮i to this full automaton via a morphism ϕi, and use (the non-appearance of) colour i to accept runs that eventually would have stayed in the safe component 𝒮i in 𝒜L𝖼𝗈𝖡. That is, the transitions of 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 that are “safe-for-colour i” will be exactly those in ϕi(𝒮i).

Formally, let 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡=(Q,SS,qinit,Δ,Γ,𝖼𝗈𝗅,𝗀𝖾𝗇𝖢𝗈𝖡) with:

  • Q={p1,p2,,pnmax},

  • qinit=p1 (any state can be chosen as initial),

  • Δ=Q×SS×Q,

  • Γ=2{1,,k}.

Finally, we define the colour labelling 𝖼𝗈𝗅:ΔΓ. For each 1ik, let ϕi:𝒮i(Q,Δ) be any injective morphism of automaton structures (such a morphism exists since |𝒮i|nmax and (Q,Δ) is the full automaton structure). We put colour i in a transition eΔ if and only if there is no transition eΔi such that ϕi(e)=e. That is, 𝖼𝗈𝗅(e)={iϕi1(e)=}.

 Remark 18.

We remark that this colour labelling uses some arbitrary choices, namely, the way we map the different safe components of 𝒜L𝖼𝗈𝖡 to the full automaton of size nmax. In particular, there is no unique minimal HD generalised coBüchi automaton recognising L. By a slight abuse of notation, we denote 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 one automaton originated by this procedure.

Example 19.

The automaton on the left of Figure 2 (page 2) (almost) corresponds to this construction. Indeed, it has been obtained by assigning a colour to each safe component of 𝒜L𝖼𝗈𝖡 (on the right) and superposing them in a 2-state automaton. To simplify its presentation, we have removed some unnecessary transitions of 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡, that is why the automaton displayed is not the full-automaton.

Proposition 20 (Correctness).

Let L be a prefix-independent language that is coBüchi recognisable. The automaton 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 is history-deterministic and recognises L.

Proof sketch.

If w admits an accepting run ρ in 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡, then its run eventually does not produce some colour i in its output. This means that, eventually, such a run is the ϕi-projection of a run in a safe component of 𝒜L𝖼𝗈𝖡, so wL. This is where we use prefix-independence: as soon as there is a witness that a suffix of w is also a suffix of a word in L, then the whole word w is in L as well.

A resolver for 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 can be defined as follows: in a round-robin fashion we follow the different safe components of 𝒜L𝖼𝗈𝖡. If a colour i is produced while we are trying to avoid it, we go back to p1 and try to avoid colour i=(i+1)modk by following the safe component 𝒮i. If a word w belongs to L, it eventually admits a safe path in 𝒜L𝖼𝗈𝖡, so it will be accepted by this resolver.

Proposition 21 (Minimality).

Let be a history-deterministic generalised coBüchi automaton recognising a prefix-independent language L. Then, |𝒜L𝗀𝖾𝗇𝖢𝗈𝖡|||.

Proof.

Let C={1,,k} be the set of output colours used by the acceptance condition of and let 𝒟CcoB be the coBüchi automaton recognising 𝗀𝖾𝗇𝖢𝗈𝖡C presented in Section 3.3. By Corollary 9, 𝒟CcoB is a history-deterministic automaton recognising L. Moreover, the states of 𝒟CcoB are a disjoint union Q1Q2Qk such that:

  • |Qi|=||,

  • all transitions leaving Qi are coBüchi transitions going to Qi+1, where Qk+1=Q1.

Therefore, each safe component 𝒮 of 𝒟CcoB is included in some Qi, so |𝒮|||. By Lemma 13, we can turn 𝒟CcoB into a nice HD coBüchi automaton satisfying that none of its safe components is larger than ||.

By Lemma 15 there is an injection η:𝖲𝖺𝖿𝖾(𝒜L𝖼𝗈𝖡)𝖲𝖺𝖿𝖾() such that |𝒮||η(𝒮)| for all safe component 𝒮 of 𝒜L𝖼𝗈𝖡. In particular, if 𝒮max is a safe component of maximal size in 𝒜L𝖼𝗈𝖡, we obtain: |𝒜L𝗀𝖾𝗇𝖢𝗈𝖡|=|𝒮max||η(𝒮max)|||. 

4.3 Minimal HD generalised coBüchi automata: general case

We now describe the polynomial-time construction for minimising a given HD generalised coBüchi automaton (without the prefix-independence assumption). For the optimality proof, we can reduce to the simplest prefix-independent case.

We fix an HD generalised coBüchi automaton 𝒜 recognising a language L. As before, using Corollary 9 and the minimisation procedure of Abu Radi and Kupferman, we can obtain the minimal HD coBüchi automaton 𝒜L𝖼𝗈𝖡 in polynomial time. We show how to convert it to an equivalent HD generalised coBüchi automaton 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 of minimal size.

Let R1,R2,,Rm be all the distinct residual languages of L, i.e., languages of the form u1L for some finite word uΣ. The case m=1 corresponds to the prefix-independent case treated in Section 4.2. We note that these residuals induce a partition of the states of 𝒜L𝖼𝗈𝖡 into QR1,,QRm, where the states in QRj recognise Rj. We assume that R1=L is the residual corresponding to the initial state of 𝒜L𝖼𝗈𝖡. Let 𝒮1,𝒮2,,𝒮k be the safe components of 𝒜L𝖼𝗈𝖡, with Si and Δi as sets of states and transitions, respectively. For each residual language Rj, define nj as the largest number of states recognising Rj appearing in a safe component of 𝒜L𝖼𝗈𝖡. That is,

nj=max1ik|SiQRj|.

We shall construct a language-equivalent HD generalised coBüchi automaton 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 with n1+n2++nm states. Towards this, for each residual language Rj, let Pj={pj1,pj2,,pjnj} be a set of nj elements. The automaton 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡=(Q,SS,qinit,Δ,Γ,𝖼𝗈𝗅,𝗀𝖾𝗇𝖡) is given by:

  • Q=P1P2Pm.

  • qinit=p11 (any state corresponding to the residual of the initial state of 𝒜L𝖼𝗈𝖡 would work).

  • Let (q,a,q) be a transition in 𝒜L𝖼𝗈𝖡, with qQRj and qQRj. Then, (p,a,p)Δ for all pPj and pPj.

  • Γ=2{1,,k}.

One way of picturing 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 is by taking the automaton of residuals of L and making nj copies of the state corresponding to each residual Rj (while keeping all transitions).

We now describe the colour labelling 𝖼𝗈𝗅:ΔΓ. Informally, each safe component 𝒮i is mapped into 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 so that the states of SiRj are mapped into Pj. These safe components are then “superimposed” upon each other and coloured appropriately, so that a run eventually staying in 𝒮i in 𝒜L𝖼𝗈𝖡 corresponds to a run in 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 that eventually avoids colour i.

More formally, for i[1,k], let ϕi:𝒮i𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 be an injective morphism such that ϕi(q)Pj if qQRj. Such injective morphism does indeed exist, by the choice of nj and the fact that 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 contains all transitions consistent with the residuals. The transitions of Δ that are i-safe are defined to be exactly those that are the image by ϕi of some transition in 𝒮i. That is, for eΔ, the labelling 𝖼𝗈𝗅(e) contains exactly the colours in {iϕi1(e)=}.

 Remark 22.

We remark that the automaton 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 obtained in this way uses a polynomial number of output colours in the size of the minimal HD coBüchi automaton 𝒜L𝖼𝗈𝖡 (see also long version). More precisely, the number k of colours is the number of safe components of 𝒜L𝖼𝗈𝖡. However, this number of colours is not necessarily optimal (see Theorem 30).

The correctness of our construction, stated below, is proven similarly to Proposition 20.

Proposition 23 (Correctness).

Let L be a coBüchi recognisable language. The automaton 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 is history-deterministic and recognises L.

In particular, the resolver for 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡 is defined as in Proposition 20: it follows the different safe components of 𝒜L𝖼𝗈𝖡 in a round-robin fashion, by trying to avoid colour some colour i while moving in ϕi(Si), then if colour i is seen it switches to i=(i+1)modk, etc.

We explain how to obtain the minimality of 𝒜L𝗀𝖾𝗇𝖢𝗈𝖡, stated below. We reduce to the prefix-independent case, using a technique from [12].333An alternative proof scheme is to extend the proof of Proposition 21 to the general case, by taking into account the residuals of the language. For this, we need a refinement of Lemma 15, stating that the injection η satisfies that, for every residual R and safe component 𝒮 of 𝒜L𝖼𝗈𝖡, |𝒮R||η(𝒮)R|. The proof of Abu Radi and Kupferman [2] does indeed lead to this result, but it is not explicitly stated in this form. Full proofs can be found in the long version.

Proposition 24 (Minimality).

Let be a history-deterministic generalised coBüchi automaton recognising a language L. Then, |𝒜L𝗀𝖾𝗇𝖢𝗈𝖡|||.

For each residual R=u1L𝖱𝖾𝗌(L), we define the local alphabet at R, as:

SSR={vSS+[uv]=[u] and for any proper prefix v of v,[uv][v]}.

That is, if 𝒜 is a semantically deterministic automaton with states Q, then SSR is the set of words that connect states in QR. Note that in general SSR may be infinite, however this is harmless in this context, and we will freely allow ourselves to talk about automata over infinite alphabets. Also, SSR is empty if and only if all the states of QR are transient, that is, they do not occur in any cycle of the automaton. For simplicity, in the following we assume that no state of 𝒜 is transient; the general case is treated in detail in the long version.

We define the localisation of L to a residual R𝖱𝖾𝗌(L) as the language over the alphabet SSR given by: LR={wSSRωwR}.

 Remark 25.

For every residual R, LR is a prefix-independent language. It corresponds to infinite words whose letters are in SSR that is, going from QR to QR, and eventually avoid seeing some colour on such paths. The prefix-independence of LR follows from the fact that LR has only itself as residual, on alphabet SSR.

Let 𝒜 be a semantically deterministic generalised coBüchi automaton with k colours recognising LSSω. For each recurrent residual R of L we define 𝒜R to be the generalised coBüchi automaton over SSR given by:

  • the set of states is QR, that is, the set of states of 𝒜 recognising R.

  • the initial state is arbitrary,

  • the acceptance condition is 𝗀𝖾𝗇𝖢𝗈𝖡C (for C the output colours of 𝒜),

  • there is a transition qw:Xp, with wSSR, X2{1,,k}, if there is a path from q to p labelled w and producing the set of colours X in 𝒜.

Lemma 26.

The automaton (𝒜R)q recognises LR for each qQR. Moreover, if 𝒜q is history-deterministic, so is (𝒜R)q.

Using the fact that (safe) paths between states in QR are the same in 𝒜 or in 𝒜R, combined with Lemma 15, we can prove:

Lemma 27.

𝒜L𝖼𝗈𝖡R is a minimal HD coBüchi automaton recognising LR. Moreover, a maximal safe component of this automaton has size nj.

To conclude the proof of Proposition 24, we combine Lemma 27 with Proposition 21 to show that |QRj|nj. This implies: ||n1++nm=|𝒜L𝗀𝖾𝗇𝖢𝗈𝖡|.

5 NP-completeness of minimisation of deterministic and HD generalised Büchi automata

In this section we contrast the polynomial-time complexity previously obtained for minimising history-deterministic generalised coBüchi automata with the 𝖭𝖯-hardness of the minimisation of deterministic generalised (co)Büchi and history-deterministic generalised Büchi automata.

Theorem 28.

The following problem is 𝖭𝖯-complete: Given a history-deterministic generalised Büchi automaton 𝒜 and a number n, decide whether there is an equivalent history-deterministic generalised Büchi automaton with at most n states.

Theorem 29.

The minimisation of the number of states of deterministic generalised Büchi and deterministic generalised coBüchi automata is 𝖭𝖯-complete.

We show 𝖭𝖯-hardness of the minimisation problems in the deterministic and history-deterministic Büchi cases simultaneously. The 𝖭𝖯-hardness for the deterministic coBüchi case follows directly. Our reduction is from a suitable version of the 3-colouring problem.

We further consider the problem of minimising both colours and states simultaneously for generalised (co)Büchi automata. For the automata classes appearing in the previous theorems (deterministic and history-deterministic generalised Büchi automata), it easily follows that this problem is 𝖭𝖯-complete. We focus therefore in the case of history-deterministic generalised coBüchi, for which the minimisation of states has proven to be polynomial (Theorem 11). We show that, even in this case, minimising both states and colours is 𝖭𝖯-complete.

Theorem 30.

The following problem is 𝖭𝖯-complete: Given a history-deterministic generalised coBüchi automaton 𝒜, and numbers n and k, decide whether there is an equivalent history-deterministic generalised coBüchi automaton with at most n states and k colours.

We obtain the lower bound by adapting the proof of 𝖭𝖯-hardness of the minimising of Rabin pairs, given in [19], itself inspired from [28]. Details can be found in the long version.

5.1 Containment in 𝗡𝗣 and bounds on the necessary number of colours

In this section we address an important subtlety of our minimisation problems: We minimise the number of states, but the number of colours used by a generalised Büchi or generalised coBüchi automaton may be exponential in its number of states.

In order to show that the problems at hand are in 𝖭𝖯, we need to show that the minimal deterministic and history-deterministic automata require a number of colours that is polynomial in the size of the input (that is, the number of states and colours of the input automaton). This turns out to be true, although not trivial. Full proofs are in the long version.

Lemma 31.

Let 𝒜 be a deterministic generalised Büchi automaton with n states and k colours. Then there is an equivalent deterministic generalised Büchi automaton with a minimal number of states and using O(n2k) colours.

Lemma 32.

Let 𝒜 be a history-deterministic generalised Büchi automaton with n states and k colours. Then there is an equivalent history-deterministic generalised Büchi automaton with a minimal number of states and using O(n3k2) colours.

This allows us to obtain an 𝖭𝖯 algorithm as we only need to guess an automaton with polynomially many states and colours, and check equivalence with the input automaton. The latter test can be done in polynomial time (see for instance [40, Thm. 4]).

As an additional result, we show that the previous lemmas do not hold for general non-deterministic automata: minimising an automaton may blow up its number of colours.

Proposition 33.

There exists a family of non-deterministic generalised Büchi automata (𝒜n)n such that for all n, 𝒜n uses n+1 states and 2 colours and a minimal automaton equivalent to 𝒜n requires 2n colours.

5.2 Hardness of state minimisation

We provide a reduction from the 3-colouring problem. We construct from a given graph G a deterministic automaton 𝒜G such that:

  • If G is 3-colourable then there is a 3-state deterministic automaton equivalent to 𝒜G, and

  • if G is not 3-colourable then there is no automaton (deterministic or not) with 3 states equivalent to 𝒜G.

This establishes the hardness of state-minimisation for deterministic and history-deterministic automata simultaneously. The full proof is in the long version. We only present here the languages we use and a sketch of the first item. The second item is obtained by a refined case analysis over the cycles of generalised Büchi automata with three states.

Given an undirected graph G=(V,E), we define the neighbourhood of a vertex v as the set N[v]={vV{v,v}E}, and its strict neighbourhood as n(v)=N[v]{v}.

We consider the alphabet SS=V. For each vV, we define the language:

Lv=(Vvv)ω(V(VN[v]))ω and we let LG=vVLv.

In words, a sequence of nodes is in LG if for all vV it either has infinitely many factors vv or sees a vertex that is not a neighbour of v infinitely many times.

The first item is proven by the following more general lemma. We actually show that from a k-colouring of G we can build a deterministic automaton with k states for LG. This also allows us to construct the automaton 𝒜G by applying this lemma on a trivial |V|-colouring.

Lemma 34.

For all graph G=(V,E) and k, if G is k-colourable then there exists a complete deterministic generalised Büchi automaton with k states which recognises LG.

Proof sketch.

Suppose G is k-colourable, let c:V{1,,k} be a k-colouring of G. We define the deterministic generalised Büchi automaton as follows:

  • The set of states is Q={1,,k}, we pick any state as the initial one.

  • For qQ and vSS=V, the v-transition from q is q𝑣c(v).

  • The set of output colours is V, hence the output alphabet is Γ=2V.

  • If qc(v), the transition q𝑣c(v) is coloured with VN[v]. Transitions of the form c(v)𝑣c(v) are coloured with Vn(v).

It is then quite straightforward to show that a word is accepted by if and only if for each v it goes infinitely many times through the v-loop on c(v) or sees infinitely many times vertices outside of N[v]. The structure of the automaton ensures that those words are exactly the ones in Lv. In particular, the fact that c(u)c(v) for all neighbours u and v implies that we cannot go through the v loop on c(v) without reading a v or a non-neighbour of v just before. Figure 3 shows an example of this construction.

Figure 3: A graph with a 3-colouring, and the corresponding automaton as defined in Lemma 34. The output colours a,b,c,d have been replaced by 1,2,3,4 for readability.

6 Conclusion

We believe that one of the key novel insights of this work is to compare the complexity of the minimisation of HD generalised coBüchi automata (polynomial) with both HD generalised Büchi automata and deterministic models (𝖭𝖯-complete). For history-deterministic and deterministic Büchi automata the minimisation problem is still open; our results are an important step in this direction, and seem to indicate that the polynomial-time minimisation algorithm for the HD coBüchi case will not extend to the Büchi or the deterministic case.

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