Modal μ-calculus explained

In theoretical computer science, the modal μ-calculus (, Lμ, sometimes just μ-calculus, although this can have a more general meaning) is an extension of propositional modal logic (with many modalities) by adding the least fixed point operator μ and the greatest fixed point operator ν, thus a fixed-point logic.

The (propositional, modal) μ-calculus originates with Dana Scott and Jaco de Bakker,[1] and was further developed by Dexter Kozen[2] into the version most used nowadays. It is used to describe properties of labelled transition systems and for verifying these properties. Many temporal logics can be encoded in the μ-calculus, including CTL* and its widely used fragments - linear temporal logic and computational tree logic.[3]

An algebraic view is to see it as an algebra of monotonic functions over a complete lattice, with operators consisting of functional composition plus the least and greatest fixed point operators; from this viewpoint, the modal μ-calculus is over the lattice of a power set algebra.[4] The game semantics of μ-calculus is related to two-player games with perfect information, particularly infinite parity games.[5]

Syntax

Let P (propositions) and A (actions) be two finite sets of symbols, and let Var be a countably infinite set of variables. The set of formulas of (propositional, modal) μ-calculus is defined as follows:

\phi

and

\psi

are formulas, then

\phi\wedge\psi

is a formula;

\phi

is a formula, then

\neg\phi

is a formula;

\phi

is a formula and

a

is an action, then

[a]\phi

is a formula; (pronounced either:

a

box

\phi

or after

a

necessarily

\phi

)

\phi

is a formula and

Z

a variable, then

\nuZ.\phi

is a formula, provided that every free occurrence of

Z

in

\phi

occurs positively, i.e. within the scope of an even number of negations.

(The notions of free and bound variables are as usual, where

\nu

is the only binding operator.)

Given the above definitions, we can enrich the syntax with:

\phi\lor\psi

meaning

\neg(\neg\phi\land\neg\psi)

\langlea\rangle\phi

(pronounced either:

a

diamond

\phi

or after

a

possibly

\phi

) meaning

\neg[a]\neg\phi

\muZ.\phi

means

\neg\nuZ.\neg\phi[Z:=\negZ]

, where

\phi[Z:=\negZ]

means substituting

\negZ

for

Z

in all free occurrences of

Z

in

\phi

.

The first two formulas are the familiar ones from the classical propositional calculus and respectively the minimal multimodal logic K.

The notation

\muZ.\phi

(and its dual) are inspired from the lambda calculus; the intent is to denote the least (and respectively greatest) fixed point of the expression

\phi

where the "minimization" (and respectively "maximization") are in the variable

Z

, much like in lambda calculus

λZ.\phi

is a function with formula

\phi

in bound variable

Z

;[6] see the denotational semantics below for details.

Denotational semantics

Models of (propositional) μ-calculus are given as labelled transition systems

(S,R,V)

where:

S

is a set of states;

R

maps to each label

a

a binary relation on

S

;

V:P\to2S

, maps each proposition

p\inP

to the set of states where the proposition is true.

Given a labelled transition system

(S,R,V)

and an interpretation

i

of the variables

Z

of the

\mu

-calculus,

[[]]i:\phi\to2S

, is the function defined by the following rules:

[[p]]i=V(p)

;

[[Z]]i=i(Z)

;

[[\phi\wedge\psi]]i=[[\phi]]i\cap[[\psi]]i

;

[[\neg\phi]]i=S\smallsetminus[[\phi]]i

;

[[[a]\phi]]i=\{s\inS\mid\forallt\inS,(s,t)\inRat\in[[\phi]]i\}

;

[[\nuZ.\phi]]i=cup\{T\subseteqS\midT\subseteq[[\phi]]i[Z\}

, where

i[Z:=T]

maps

Z

to

T

while preserving the mappings of

i

everywhere else.

By duality, the interpretation of the other basic formulas is:

[[\phi\vee\psi]]i=[[\phi]]i\cup[[\psi]]i

;

[[\langlea\rangle\phi]]i=\{s\inS\mid\existst\inS,(s,t)\inRa\wedget\in[[\phi]]i\}

;

[[\muZ.\phi]]i=cap\{T\subseteqS\mid[[\phi]]i[Z\subseteqT\}

Less formally, this means that, for a given transition system

(S,R,V)

:

p

holds in the set of states

V(p)

;

\phi\wedge\psi

holds in every state where

\phi

and

\psi

both hold;

\neg\phi

holds in every state where

\phi

does not hold.

[a]\phi

holds in a state

s

if every

a

-transition leading out of

s

leads to a state where

\phi

holds.

\langlea\rangle\phi

holds in a state

s

if there exists

a

-transition leading out of

s

that leads to a state where

\phi

holds.

\nuZ.\phi

holds in any state in any set

T

such that, when the variable

Z

is set to

T

, then

\phi

holds for all of

T

. (From the Knaster–Tarski theorem it follows that

[[\nuZ.\phi]]i

is the greatest fixed point of

T\mapsto[[\phi]]i[Z

, and

[[\muZ.\phi]]i

its least fixed point.)

The interpretations of

[a]\phi

and

\langlea\rangle\phi

are in fact the "classical" ones from dynamic logic. Additionally, the operator

\mu

can be interpreted as liveness ("something good eventually happens") and

\nu

as safety ("nothing bad ever happens") in Leslie Lamport's informal classification.[7]

Examples

\nuZ.\phi\wedge[a]Z

is interpreted as "

\phi

is true along every a-path".[7] The idea is that "

\phi

is true along every a-path" can be defined axiomatically as that (weakest) sentence

Z

which implies

\phi

and which remains true after processing any a-label. [8]

\muZ.\phi\vee\langlea\rangleZ

is interpreted as the existence of a path along a-transitions to a state where

\phi

holds.

Decision problems

Satisfiability of a modal μ-calculus formula is EXPTIME-complete.[10] Like for linear temporal logic,[11] the model checking, satisfiability and validity problems of linear modal μ-calculus are PSPACE-complete.[12]

See also

Notes

  1. Scott . Dana . Dana Scott. Bakker . Jacobus . 1969 . A theory of programs . Unpublished Manuscript.
  2. Kozen. Dexter. Results on the propositional μ-calculus. ICALP. 1982. Automata, Languages and Programming. 140. 348–359. 978-3-540-11576-2. 10.1007/BFb0012782.
  3. Clarke p.108, Theorem 6; Emerson p. 196
  4. Arnold and Niwiński, pp. viii-x and chapter 6
  5. Arnold and Niwiński, pp. viii-x and chapter 4
  6. Arnold and Niwiński, p. 14
  7. Bradfield and Stirling, p. 731
  8. Bradfield and Stirling, p. 6
  9. Book: Erich Grädel . Phokion G. Kolaitis . Leonid Libkin. Leonid Libkin . Maarten Marx . . . Yde Venema . Scott Weinstein . Finite Model Theory and Its Applications . 2007 . Springer . 978-3-540-00428-8 . 159.
  10. Book: Klaus Schneider. Verification of reactive systems: formal methods and algorithms. 2004. Springer. 978-3-540-00296-3. 521.
  11. Sistla. A. P.. Clarke. E. M.. 1985-07-01. The Complexity of Propositional Linear Temporal Logics. J. ACM. 32. 3. 733–749. 10.1145/3828.3837. 0004-5411. free.
  12. Book: Vardi, M. Y.. Proceedings of the 15th ACM SIGPLAN-SIGACT symposium on Principles of programming languages - POPL '88 . A temporal fixpoint calculus . 1988-01-01. New York, NY, USA. ACM. 250–259. 10.1145/73560.73582. 0897912527. free.

References

External links