MATHEMATICAL MODAL LOGIC: A VIEW OF ITS EVOLUTION
MATHEMATICAL MODAL LOGIC: A VIEW OF ITS EVOLUTION MATHEMATICAL MODAL LOGIC: A VIEW OF ITS EVOLUTION
70 Robert GoldblattThe logic CTL* was defined semantically, and a sound and complete axiomatisationof it was hard to find. Eventually one was provided by Mark Reynolds[2001].A property of paths not expressible in linear time logic, or even in CTL*, isthat a formula be true at every even state along the path (and possibly at others).Sets of sequences that have this property can be generated by formal grammars, orcharacterised by finite-state automata that process infinite strings. Pierre Wolper[1983] showed that any regular grammar gives rise to a temporal connective creatingformulas that are true just of paths generated by that grammar in a certainway. He also showed that the linear time connectives G, F , X and U can eachbe expressed by such a grammar, and dubbed this formalism ETL for “ExtendedTemporal Logic”. The idea can be applied to branching time systems, and leadsto a logic ECTL* into which CTL* can be translated (see [Thomas, 1989]).Surveys of computational temporal logic, and its various applications to reasoningabout programs, are given in [Emerson, 1990] and [Stirling, 1992].A different kind of use of modalities of the branching-time type was made byGlynn Winskel [1985] in constructing powerdomains. These structures arise in thedenotational semantics of programs, and are intended to provide domain-theoreticanalogues of powersets. In dynamic logic a non-deterministic program is modelledas a binary transition relation R on a set S of possible program states. Alternativelythis can be viewed as a function from S to its powerset P(S), taking eachstate x ∈ S to the set {y : xRy} of states that can be reached by different possibleexecutions of the program. Analogously, given a domain D, a non-deterministicprogram may be modelled as a function from D to its powerdomain.There are several different powerdomain constructions, and Winskel shows howto build them out of formulas of some modal languages associated with D. Thisinvolves tree-like models of the languages that represent certain computations.For the “Smyth” powerdomain a modality ✷ is used that it read “inevitably”. ✷αhas the same meaning in these models as the CTL-modality ∀F α, i.e. along everyfuture path there is a state at which α holds. The construction of the “Hoare”powerdomain uses ✸, for “possibly”, with ✸α meaning that there is a future pathwith α true somewhere, i.e. ∃F α. For the “Plotkin” powerdomain, both of thesemodalities are involved.7.4 The Modal µ-CalculusMathematics and computer science abound with concepts and objects that aredefined recursively, or self-referentially. Many of these have an elegant formulationas special fixed points of certain operations. The µ-calculus L µ of Kozen [1982;1983] admits formulas that are interpreted as fixed points, and is expressively morepowerful than any of the modal program logics considered above.Let Θ : P(S) → P(S) be an operation on the powerset of a set S. Tarski appliedthe term “fixpoint” to any subset T of S such that Θ(T ) = T . If Θ is monotonic
Mathematical Modal Logic: A View of its Evolution 71in the sense that T ⊆ T ′ implies Θ(T ) ⊆ Θ(T ′ ), then Θ has a least fixpoint µΘand a greatest fixpoint νΘ, given byµΘ = ⋂ {T ⊆ S : Θ(T ) ⊆ T },νΘ = ⋃ {T ⊆ S : T ⊆ Θ(T )}.The fact that Θ has a fixpoint was first shown by Tarski and B. Knaster in 1927.In 1939 Tarski generalised this to any monotonic function on a complete lattice,showing that its fixpoints also form a complete lattice, with greatest and leastelements specified by the lattice versions of the definitions just given (see [Tarski,1955b] for this historical background).Pratt [1981] introduced the idea of using a “minimisation” operator in a PDLlikecontext, but interpreted µ as a least root operator rather than a least fixpointone. He developed a language of terms intended to denote elements of a Booleanalgebra, with a term of the form µQ.τ(Q) interpreted as the least solution of theequation “τ(Q) = 0”. A syntactic restriction was imposed on τ to ensure thatat least one solution exists. A translation of PDL into the resulting calculus wasgiven, and the system was shown to have the finite model property by a refinementof the McKinsey method. A deterministic exponential time algorithm was givenfor the problem of deciding satsfiability terms.Pratt’s work provided the inspiration for Kozen’s development of the calculusLµ, whose language is generated from some collection Π of atomic programs (oraction labels) π. Lµ-formulas are constructed from propositional variables usingthe truth-functional connectives, the modalities [π] and 〈π〉 for π ∈ Π, and theconstructions µp.α and νp.α, where p is a propositional variable and α is a formula.The operations µp and νp function like quantifiers, binding occurrences of p in α.µp.α and νp.α are only allowed to be formed when α is positive in the sense that allfree occurrences of p in α are within the scope of an even number of negations ¬.This condition is satisfied for instance by any formula constructed from variablesusing only ⊤, ⊥, ∧, ∨, [π], 〈π〉, µp and νp. The “binder” ν is definable in terms ofµ by taking νp.α as ¬µp.¬α(¬p/p). Vice versa, µ could be defined in terms of ν.An Lµ model M = (S, { π −→: π ∈ Π}, Φ) is just like a Kripke model for dynamiclogic, or a labelled transition system for Hennessy–Milner logic augmented by avaluation Φ to interpret the variables p. M gives each formula α the interpretationM(α) = {x ∈ S : M |= x α}. If α contains the variable p, then varying theinterpretation of p causes the interpretation of α to vary, and in this way α inducesan operation on P(S). To make this precise, for T ⊆ S let M p:=T be the modelthat is identical to M except in interpreting p as T , i.e. M p:=T (p) = T . Then theoperation induced by α on P(S) relative to M is the functionΘ M α: T ↦−→ M p:=T (α).If α is positive, then Θ α is monotonic. Assuming inductively that Θ α has beenspecified, M(µp.α) and M(νp.α) are defined to be the least and greatest fixpointsµΘ M α and νΘ M α given by the Tarski–Knaster Theorem.
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Mathematical Modal Logic: A View of its Evolution 71in the sense that T ⊆ T ′ implies Θ(T ) ⊆ Θ(T ′ ), then Θ has a least fixpoint µΘand a greatest fixpoint νΘ, given byµΘ = ⋂ {T ⊆ S : Θ(T ) ⊆ T },νΘ = ⋃ {T ⊆ S : T ⊆ Θ(T )}.The fact that Θ has a fixpoint was first shown by Tarski and B. Knaster in 1927.In 1939 Tarski generalised this to any monotonic function on a complete lattice,showing that its fixpoints also form a complete lattice, with greatest and leastelements specified by the lattice versions of the definitions just given (see [Tarski,1955b] for this historical background).Pratt [1981] introduced the idea of using a “minimisation” operator in a PDLlikecontext, but interpreted µ as a least root operator rather than a least fixpointone. He developed a language of terms intended to denote elements of a Booleanalgebra, with a term of the form µQ.τ(Q) interpreted as the least solution of theequation “τ(Q) = 0”. A syntactic restriction was imposed on τ to ensure thatat least one solution exists. A translation of PDL into the resulting calculus wasgiven, and the system was shown to have the finite model property by a refinementof the McKinsey method. A deterministic exponential time algorithm was givenfor the problem of deciding satsfiability terms.Pratt’s work provided the inspiration for Kozen’s development of the calculusLµ, whose language is generated from some collection Π of atomic programs (oraction labels) π. Lµ-formulas are constructed from propositional variables usingthe truth-functional connectives, the modalities [π] and 〈π〉 for π ∈ Π, and theconstructions µp.α and νp.α, where p is a propositional variable and α is a formula.The operations µp and νp function like quantifiers, binding occurrences of p in α.µp.α and νp.α are only allowed to be formed when α is positive in the sense that allfree occurrences of p in α are within the scope of an even number of negations ¬.This condition is satisfied for instance by any formula constructed from variablesusing only ⊤, ⊥, ∧, ∨, [π], 〈π〉, µp and νp. The “binder” ν is definable in terms ofµ by taking νp.α as ¬µp.¬α(¬p/p). Vice versa, µ could be defined in terms of ν.An Lµ model M = (S, { π −→: π ∈ Π}, Φ) is just like a Kripke model for dynamiclogic, or a labelled transition system for Hennessy–Milner logic augmented by avaluation Φ to interpret the variables p. M gives each formula α the interpretationM(α) = {x ∈ S : M |= x α}. If α contains the variable p, then varying theinterpretation of p causes the interpretation of α to vary, and in this way α inducesan operation on P(S). To make this precise, for T ⊆ S let M p:=T be the modelthat is identical to M except in interpreting p as T , i.e. M p:=T (p) = T . Then theoperation induced by α on P(S) relative to M is the functionΘ M α: T ↦−→ M p:=T (α).If α is positive, then Θ α is monotonic. Assuming inductively that Θ α has beenspecified, M(µp.α) and M(νp.α) are defined to be the least and greatest fixpointsµΘ M α and νΘ M α given by the Tarski–Knaster Theorem.