Introduction
Modal logics were created so we can express ideas like the following
without having to use quantifiers and variables:
- For all time, at some time, never, ...
- For all future time, at some time in the past...
- X wants ... to be true.
- At all places....
- In all possible worlds...
- In some worlds...
- It is impossible...
- In all subsystems....
- As long as other subsystems don't do X this system will do Y.
These ideas are called modes.
There are a large number of logics that attempt to model them.
They date back to
Aristotle (of course). These early thinkers rapidly realized that
the meaning of "at some time, the sky will fall" depends on
whether the future is pre-determined or full of possibilities.
The different models of time and different modes
of expression came under intense formal study
in the twentieth century for three reasons: (1) to find a
logic where "if _ then _" behaved more intuitively, (2) because
the modal system were there, and (3) because they looked as if they
might be useful in thinking about complex computerized systems.
When computerizing complex high risk situations we need to be very
clear about what we are asking for. If we want the system to exhibit some
property in every possible state, and for all time, then
we don't want it merely, at all time, have the option of
fulfilling the property sometimes. English is not very good at expressing
such distinctions. Studying modal logics uncovers the half-a-dozen
different ways we may want a piece of software to have a property.
Some modal logics make it easy to calculate whether the logical behavior
of a piece of software (a model) satisfies its requirements.
Notice that it is useful to be able to reason about time varying
properties of complex computerized systems. Indeed checking that
software fits such properties has uncovered some difficult
to find bugs in real software. However the normal notation
is somewhat clumsy and so there has been research on graphic
notations ( GIL:
[ citation.cfm?id=192218.192226&coll=portal&dl=ACM&idx=J790&part=transaction&WantType=transaction&title=ACM%20Transactions%20on%20Software%20Engineering%20and%20Methodology%20%28TOSEM%29&CFID=1643654&CFTOKEN=8691090 ]
and Buchi automata (
[click here
if you can fill this hole]
)). A tabular form might also work well.
[click here
if you can fill this hole]
The modalities based on the Propositional Calculus (PROPOSITION)
are not problematic. For example you can get a simple extension
that lets you talk about "all possibly computations" without having
to have any quantified variables: "for all x....".
When quantifiers and equality are introduced as well as
modalities, some
interesting things can occur. In particular there is a loss of
referential transparency: you can no longer substitute equals for
equals. For example in the mode of "wanting things to be true":
Hamlet may want the person behind curtains dead, but he does
not want Polonius to die, even though Polonius is the person
hiding behind the curtains.
Another bad effect of combining modes and quantifiers
is that some expressions become ambiguous
[FittingMendelsohn98]
because modes have no explicit scope or variables. The standard
MATHS notation has predicates and quantifiers and so
the standard approach to modes in the MATHS notation is to
treat them explicitly as quantifiers. This sacrifices
simplicity on the altar of accuracy. Thus instead of
being able to write
[]p
one must write
for all t:Time(p(t)).
This is longer but more precise. The precision is only
important if p(t) includes other variables and quantifiers.
However MATHS permits operators to operate on predicates
like p above as well as on Boolean propositions so we could
define
For P:Time->@, always(P) ::= for all t:Time(P(t)).
and get the apearance of a modal logic within the MATHS system.
Michael Jackson's recent work has another approach for mapping temporal modes
into the lower predicate calculus.
This seems to be the approach taken to modeling time in the
SUMO ontology:
[ logic_8_Natural_Language.html#SUMO ]
[ Browse.jsp?kb=SUMO&term=time ]
This approach has been taken further by introducing a token
that identifies events which links them to Places and Times, see
next subsection.
Event-token reification for spatial-temporal modes
Source
[ http://plato.stanford.edu/entries/logic-temporal/ ]
Donald Davidson (1967). The problem is to give a formal account of the validity of such inferences as
- John saw Mary in London on Tuesday.
- Therefore, John saw Mary on Tuesday.
The inference above is cast in logical form as
- for some e(See(John,Mary,e) & Place(e,London) & Time(e,Tuesday)),
- Therefore, for some e(See(John,Mary,e) & Time(e,Tuesday)).
Also see the Event Calculus of Kowalski and Sergot (1986).
Partly Baked Ideas
Net
May be basis of Jackson's model of time as a series of
alternating events and intervals with no events?
Very flexible -- allows the same logic to handle many different temporal epistimologies by adjusting Time and Place.
Also... event tokens could act as objects:
- Jim saw John seeing Mary in London on Tuesday.
- for some e1,e2 (See(Jim, e1, e2) & See(John,Mary,e1) & Place(e1,London) & Time(e1,Tuesday)).
Perhaps an axiom
- for all e1,e2, p, t, See(Jim, e1, e2), See(John,Mary,e1) & Place(e1,p) & Time(e1,t)(Place(e2,p) & Time(e2,t)).
Also compare Babel 17[Delaney] where events are given a verbal tag for future reference.
The next level of generality is to reify the verbs:
- for some e(Event(e, see, John, Mary) & Place(e, London) & Time(e, Tuesday)).
This then permits statements at the meta level:
- for all x, Event(x, isa, see, verb).
(End of Net)
The traditional presentation of a logic is to:
- Describe the syntax of the well formed formula.
- Describe the axioms and derivation rules.
- Present a semantic model using formal mathematics
Sites Worth a visit
Garson, James, "Modal Logic", The Stanford Encyclopedia of Philosophy
(Winter 2001 Edition), Edward N. Zalta (ed.), URL =
<http://plato.stanford.edu/archives/win2001/entries/logic-modal/>
[ http://plato.stanford.edu/entries/logic-modal/ ]
(philosophical but thorough).
Animations of several logics with instructions in Dutch:
[ http://plato.stanford.edu/entries/logic-modal/ ]
(Easier to figure out than you might think...)
Simple Temporal Logics
THe following are just to illustrate how I would approach
constructing modalities within my MATHS system.
The MATHS approach is:
- Define a syntax and semantics using MATHS.
- Derive useful and interesting properties and rules.
The following are some samples of modal propositional logics.
Simple Temporal Logic
- SIMPLE_TEMPORAL_LOGIC::=following,
Net
We start with presuming that there is such a thing as Time:
- Time::Sets.
We assume time is an ordered:
- |-POSET(Time, strict=>before, strict_inverse=>after).
We are interested in expressions that map Time into true and false values:
- P::=@^Time.
The propositions P are things that are true or false at particular times:
`The sun is shining`
`It is raining`.
If we supply a time then we assume that we can be sure that a proposition
is either true or false at that time. So, suppose
p:=it is raining,
and
- today:Time,
then
p(today) = today, it is raining.
Note.
The above presumes that we can be definite about the state of our
propositions at any given time. Other temporal logics do not
make this assumption.
We can define boolean operations on such propositions:
- not:: P->P = map[p:P}(map[t:Time](not p(t)).
not p is true at any time p is false and vice versa.
- and:: infix(P,P,P) = map[p,q:P](map[t:Time](p(t) and q(t) ),
p and q at time t iff p is true at t and q is true at t.
- or:: infix(P,P,P) = map[p,q:P](map[t:Time](p(t) or q(t) ),
p or q at time t iff either p is true at t or q is true at t.
- For p,q, if p then q::= ((not p) or q ),
At time t (if p then q is true) iff at time t( q is true or p is false).
So, for example
not(`It is raining` and `The sun is shining`).
Then add the modal operator everafter:
- everafter:: P->P= for all Time t where t after (_) ( p(t) ),
that indicates that after this time, the proposition is always true.
Note that unlike most modal operators, we do not induce the present
as part of the future because we use the strict ordering after.
For example
everafter `sun shines in San Bernardino`.
Define sometime as a modal operator:
- sometime:: P->P= for some Time t where t after (_) ( p(t) ),
indicating that at some time now or later the proposition is true.
For example
sometime `it rains in Manchester`.
We can rapidly show:
- (sometime, everafter, not)|- (T1): sometime = not everafter (not).
- (everafter, sometime)|- (T2): For p:@^Time, if everafter(p) then sometime(p).
- (everafter, sometime)|- (T3): If p=Time+>true then everafter p and sometime p.
Notice this intuitive interpretation of the combined modallity:
everafter sometime =(_) is true infinitely often, eternal recurrence.
Also notice we have a spoeical modal implication:
p being true everafter leads to q being true later.
It behaves in this logic very like the normal if_then_ in PC or LPC.
It is defined like this:
- For p,q:P, p~>q::P = everafter( if p then sometime q),
at any time, if p is true then at some time after that q will be true.
(End of Net
SIMPLE_TEMPORAL_LOGIC)
Simple Discrete Temporal Logic
The SIMPLE_TEMPORAL_LOGIC makes view assumptions about the structure of time.
If the time was discrete then it would consist of a series of instances.
Each time would be followed by another time. Hence we can talk about a
property being true in the next instant as well as for all time or at some
future time.
- SIMPLE_DISCRETE_TEMPORAL_LOGIC::=following,
Net
We start by importing all the formulae, assumptions, and theorems
of the simple logic. Then we add assumptions that restrict time
to being discrete.
- |- (STL): SIMPLE_TEMPORAL_LOGIC.
- next:: Time---Time.
- |- (discrte): for all t:Time, next(t) after t.
For example to talk about the weather:
tomorrow = next( today).
We next introduce a modal operator that maps a temporal property one
instance into the future:
- For p:P, next_time(p)::= map[t](p(next (t))).
- (next_time)|-next_time = map[p] (p o next).
We can then show properties like
- (above)|- (nn): not next_time = next_time not.
- (above)|- (sn): sometime next_time = next_time sometime.
- (above)|- (an): everafter next_time = next_time everafter.
- (above)|- (ns): if next_time p then sometime p.
- (above)|- (en): if ever_after p then next_time p.
- (above)|- (nand): next_time(p and q) = (next_time p) and (next_time q).
and so on...
Can we show:
- sometime p = next_time p or sometime next_time p.
- everafter p = next_time p and everafter next_time p.
Or do we need an induction axiom?
[click here
if you can fill this hole]
(End of Net
SIMPLE_DISCRETE_TEMPORAL_LOGIC)
. . . . . . . . . ( end of section Simple Temporal Logics) <<Contents | End>>
Linear Temporal Logic
Linear temporal logic(LTL) is a popular language for verifying properties of
complex safety-critical systems. It can be used as part of the SPIN tool
to describe requirements. A language called Promela is used to describe how
the system evolves. SPIN varifies that the Promela model of the system
satisfies the requirement.
Summary
| Name | Symbol | Example | Meaning | Pattern
|
|---|
| and, or, not | /\,\/,- | p/\q | PC | -
|
| always | [] | []p | For all future time p | p,p,p,p,p,p...
|
| sometime | <> | <>p | At some future time p | -p,-p,-p,-p,p,...
|
| next | () | ()p | In the next instant p | -p,p,...
|
| until | U | (p U q) | q becomes true and before then p is always true. | p,p,p,p,q,...
|
Details
- LTL::=following,
Net
[click here
if you can fill this hole]
(End of Net
LTL)
LTL in Practice
[HavelunddLowryPenix01]
. . . . . . . . . ( end of section Linear Temporal Logic) <<Contents | End>>
Computational Tree logic
This is a popular logic for proving properties of non-deterministic
concurrent programs and circuits. It assumes time is discrete: each state
is followed by anther state at the next interval of time. It does not
assume that each state is followed by a only one state. Thus, suppose
that the current state can be followed by states a, b, and c and that
p is true in all of these states, but q is true in only state b then
we can assert that AX p(all next) and EX q(exists next). We can not
assert AX q since q is not true in All neXt states. Here is
an informal picture of the semantics of CTL, followed by a more
formal presentation.
- CTL::=following,
Net
[HuthRyan00]
Syntax
- w::=wff, from PC.
Add the following operators.
- AX::w->w=all next.
- EX::w->w=some next.
- AG::w->w=all possibilities forever.
- EG::w->w=some possibility forever, There is a infinite path....
- AF::w->w=all possibilities sometime.
- EF::w->w='some possibility sometime.
- AU::w><w->w=always until, -- AU(p,q) requires q to be true at some time and p true at all previous times.
- AW::w><w->w=weak always until, -- does not require q to be true, but if it iis (at some future time) then p must be true up until that time.
- EU::w><w->w=sometime until.
Semantic Model
The semantics is in terms of a model M and a state s
of that model.
The Model M has states, a next relationship, and
a labelling relation that maps states into sets
of propositions. This is used to define satisfaction:
that in the model, starting at the state, the formula is
true.
- MODEL::=
Net{
- States::@Sets.
- next::@(States, States).
- |- (nodeadstate): for all s:States( next(x)<>{} ).
- Wff::Propositions.
- label::States->Wff.
- For s:States, Paths(s)::@#States={p:# States. p[1]=s and for all (s,s'):p (s next s')}.
- satisfies::States><wff>->@.
- satisfices::wff->@States = map[p]{s:States. satisfies(s,p)}.
- |-satisfies(s, p) iff p in label(s).
- |-satisfies(s, not p) iff p not in label(s).
- |-satisfies(s, p and q) iff (p in label(s) and q in label(s)).
- |-satisfies(s, p or q) iff (p in label(s) or q in label(s)).
- |-satisfies(s, AX(p)) iff for all s':next(s)(satisfies(s',p)).
- |-satisfies(s, EX(p)) iff for some s':next(s)(satisfies(s',p)).
- |-satisfies(s, AG(p)) iff for all P:Paths(s)(P ==> satisfices(p)).
- |-satisfies(s, AF(p)) iff for all P:Paths(s)(P and satisfices(p)).
- |-satisfies(s, EG(p)) iff for some P:Paths(s)(P ==> satisfices(p)).
- |-satisfies(s, EF(p)) iff for some P:Paths(s)(P and satisfices(p)).
- |-satisfies(s, AU(p,q)) iff for all P:Paths(s), some i:1..#P-1(satisfies(P[i+1], q) and P[1..i] ==> satisfices(p)).
- |-satisfies(s, EU(p,q)) iff for some P:Paths(s), some i:1..#P-1(satisfies(P[i+1], q) and P[1..i] ==> satisfices(p)).
- AW(p, q)::=not EU( not q, (not p and not q)).
}=::
MODEL.
Text book notation
| MATHS | Text
|
|---|
| and
|
|
| or
|
|
| not
|
|
| AU(p,q) | A[p U q]
|
| EU(p,q) | E[p U q]
|
| AW(p,q) | A[p W q]
|
Note. The GIFs of the logic symbols above were downloaded from
Michael Huths excellent web site at
[ http://www.cis.ksu.edu/~huth/lics/ ]
for the "Logic in Computer Science" text book authored with
Mark Ryan.
SMV notation
The Simple Model Verifier (SMV) has a different notation:
| MATHS | SMV
|
|---|
| and | &
|
| or | |
|
| not | !
|
| AU(p,q) | A[p U q]
|
| EU(p,q) | E[p U q]
|
Properties
Certain interesting and/or useful properties follow
from the MODEL.
As a rule the future includes the present:
- if p then EF(p).
- if p then EG(p).
Universallity implies existance
- if AG(p) then EG(p).
- if AF(p) then EF(p).
- if EG(p) then EF(p).
- ...
Until X implies X at some time:
- AU(p,q) = AW(p, q) and AF(q).
Equivalences
- |- (dm1): not o AF = EG o not.
- |- (dm2): not o EF = AG o not.
- |- (dm3): not o AG = EF o not.
- |- (dm4): not o EG = AF o not.
- |- (dmx): not o EX = AX o not.
- |- (auaf): AF = AU( true, (_) ).
- |- (euef): AF = EU( false, (_) ).
The following look like recursive or inductive definitions:
- |- (agx): AG = (_) and AX AG(_)).
- |- (egx): EG = (_) and EX EG(_)).
- |- (afx): AF = (_) or AX AF(_)).
- |- (efx): EF = (_) or EX EF(_)).
- |- (eux): EU = (2nd) or ((1st) and EX EU( (1st), (2nd) )) ).
- EU(p,q)= q or ( p and EX EU(p,q).
- |- (aux): AU = (2nd) or ((1st) and AX AU( (1st), (2nd) )) ).
TBD
(End of Net
CTL)
Practical Examples
Web sites
- PATTERNS::= See http://www.cis.ksu.edu/santos/spec-patterns/ctl.html.
. . . . . . . . . ( end of section Computational Tree logic) <<Contents | End>>
Propositional Temporal Logic
The following comes from a paper that summarizes the conclusions
of 20 years research into a modal logic for talking about
step-by-step computations
[ LichtensteinPnueli00 ]
that describes the PTL and proves lots of results both within
PTL and about PTL.
- PTL::=Propositional_Temporal_Logic.
- Propositional_Temporal_Logic::=following,
Net
- wff::Syntax, well formed formula of the PTL.
- |-PROPOSITIONS(simple_proposition=>wff).
- next::wff->wff.
- prev0::wff->wff.
- until::infix(wff).
- since::infix(wff).
- prev::= not prev0 not.
- eventually::= true until (_).
- once::= true since (_).
- henceforth::= not eventually not.
- sofar::= not once not.
- p waitingfor q::=(henceforth p) or (p until q).
- p backto q::=(sofar p) or (p since q).
- p entails q::=henceforth(if p then q).
- p equiv q::=henceforth( p iff q).
- |- (F0): if henceforth p then p.
- |- (F1): next not p equiv not next p.
- |- (F2): next(if p then q)entails(if next p then next q).
- |- (F3): henceforth(if p then q)entails(if henceforth p then henceforth q).
- |- (F4): if henceforth p then henceforth next p.
- |- (F5): if p entails next p then p entails henceforth p.
- |- (F6): p until q equiv (q or (p and next (p until q))).
- |- (F7): p until q entails eventually q.
- |- (P1): prev p entails prev0 p.
- |- (P2): prev0(if p then q )entails if prev0 p then prev0 q.
- |- (P3): if henceforth p then henceforth prev0 p.
- |- (P4): (p since q)equiv(q or(p and prev(p since q)) ).
- |- (P5): prev0 false.
- |- (M8): p entails next prev0 p.
all tautologies and inference rules in PROPOSITIONS are inherited along with modus ponens.
The original paper
[ LichtensteinPnueli00 ]
proves many theorems that hold in this logic.
[click here
if you can fill this hole]
(End of Net
Propositional_Temporal_Logic)
- PTL_MODEL::= following,
Net
- S::Sets.
- interpretation::=propositions->@S, the set of states in which (_) is true.
- computation::=Nat0 -> S.
- model::=computation><interpretation.
- triple::=computation><interpretation><Nat0.
- satisfies::@(triple,wff).
- |-( (s,I,j) satisfies true) and not ( (s,I,j) satisfies false).
- |-for P:proposition( (s,I,j) satisfies P iff s[] in I(P)).
- ...
- |-( (s,I,j) satisfies p until q) iff for some k:j.. ((s,I,k) satisfies q and for all i:j..k-1 ((s,I,i) satisfies p)).
- |-( (s,I,j) satisfies next p) iff (s,I,j+1) satisfies p).
- |-( (s,I,j) satisfies prev0 p) iff j=0 or j>0 and (s,I,j-1) satisfies p).
- |-( (s,I,j) satisfies p since q) iff for some k:0..j ((s,I,k) satisfies q and for all i:k+1..j ((s,I,i) satisfies p)).
(End of Net
PTL_MODEL)
can show that PTL is sound and complete for PTL_MODEL.
. . . . . . . . . ( end of section Propositional Temporal Logic) <<Contents | End>>
Interval Logic
- INTERVAL_LOGIC::=
Net{
Hansen Ravn and Rischel 91
[HansenRavnRischel91].
Boolean expressions (predicates) are interpreted as describing the set of times when the formula are true. Hence interval functions and durations.
- Note: (a..b) = open interval ={x. a<x<b},
- a..b=closed interval={x. a<=x<=b},
- [a..b)=half open interval={x. a<=x<b},
- (a..b]=half open interval={x. a<x<=b},
- Times::= Real.
Interval functions
- intervals::=Times)->@.
duration(p)(b..e) ::=measure{x:b..e||p}, or equiv integral(x,b,e,if(p,1,0)).
length(b..e)=b-e=duration(x in b..e)
- duration_predicate(p)::=\ceiling(p) ::=
- map[i](duration(p)(i)=length(i)>0)
- A;B::=map[i]for some m:i(true./A==>b..m and true./B==>m..e)
- eventually(A)::=map[i](true;A;true),
- always(A)::=not o eventually(A) o not.
...
[click here
if you can fill this hole]
}=::
INTERVAL_LOGIC.
. . . . . . . . . ( end of section Interval Logic) <<Contents | End>>
TRIO Temporal Logic
Trio is a model logic that has been used to reason about complex time dependent properies of compterized system. It has a large number of modes corresponding to tenses. All derived form one simple one by using quantification over time.
[GargantiniMorzenti01]
[Federetal94a]
- TRIO::=following
Net
- Time::@Real. Normally would be the Real numbers. Note: (a..b) = open interval ={x. a<x<b}, a..b=closed interval={x. a<=x<=b), [a,b), ...
[ Intervals in math_42_Numbers ]
- |-GROUP(Time, +, -, 0). Implicitly assumes times are closed under addition.
- TDP::= Time->@,Time dependent predicate.
- For d:Time, F:TDP, Dist(F,d):: TBP= map[t]F(t+d).
- Dist(F,d) is true at time t if and only if F is true at time t+d.
- ()|- (d1): for G:=Dist(F,d), all t, G(t)=F(t+d).
- (above)|- (d2): Dist(F,d) = F((_) + d) = F o (_+d) = (_+d); F.
- Futr(F,d)::= d>=0 and Dist(F,d).
- Past(F,d)::= d>=0 and Dist(F, - d).
- Lasts(F,d)::= for all d':(0..d) (Futr(F,d)).
- Lasted(F,d)::= for all d':(0..d) (Past(F,d)).
- Alw(F)::= for all d(Dist(F,d)).
- AlwF(F)::= for all d, d>0(Dist(F,d)).
- AlwP(F)::= for all d, d>0(Dist(F, -d)).
- ()|- (a1): AlwF(F) = for all d, d>0(Futr(F,d)).
- Until(F,G)::= for some t>0( Futr(G,t) and Lasts(F, t) ).
- Som(F)::= for some d (Dist(F,d)).
- SomP(F)::= for some d, d<0(Dist(F, d)).
- UpToNow(F)::=for some d, d>0(Lasted(F,d)).
- NowOn(F)::=for some d, d>0(Lasts(F,d)).
- Becomes(F)::= UpToNow(not F) and (F or NowOn(F)), slightly different to Federeretal?
- LastTime(F,t)::=Past(F,t) and Lasted(not F, t).
- NextTime(F,t)::= Futr(F,t) and Lasts(not F, t).
- Can define closed and half closed versions of all the above!
GargantiMorzenti also define some special types of predicates.
- Events are point based: they are true at a time but not before or after:
- Event::={F. Alw( if F then UpToNow(not F) and NowOn( not F))}.
- Interval_based_predicate::= {F. Alw(if F then (UpToNow(F) or NowOn(F)) else UpToNow(not F) or NowOn(not F)))}.
- Note: if p then q else r = (if p then q) and (if not p then r).
- Left_Continuous_Interval_Based_Predicate::={F. Alw((if F then UpToNow(F)else ` UpToNow(not F)))}.
- Right_Continuous_Interval_Based_Predicate::={F. Alw((if F then NoOn(F) else UpToOn(not F)))}.
Some TDP are more likely to exist in real systems, and about which properties are easier to prove.
For example a predicate Z defined by Past(Z, t) iff for some n:1..(t=1/n) describes an event defined to occur at an infinite number of times 1, 1/2, 1/3, ... in the near past. Non-Zeno predicates are
- nonZeno(F)::@ TDP = Alw( (UpToNow(not F) or UpToNow(F)) and (NowOn(not F) or NowOn(F) ).
Note --the idea of a nonZeno predicte allows events to occur infinitely close to each other but excludes events that happen an infinite number of times.
Question: What about switch bounces?
- Many results are claimed to be proved in GargantiMorzenti01.
- They go on to define time dependent variables and other ideas useful for analyzing requirements.
(End of Net
TRIO)
Kripke Semantics
Kripke semantics provides a uniform way to interpret
the formulae of modal logics. In normal logic we have a single
domain of discourse. To model modes we envisage a collection
of logical worlds. The worlds a connected and one knows
about the connected ones. One mode is in all connected words
and the other is modeled by in some connected world. By
assuming various properties of the connection relationship
we can create a model of any well-known model logic.
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Glossary
- TBD::="To Be Done".
References and Links
- PROPOSITIONS::= See http://www.csci.csusb.edu/dick/maths/logic_10_PC_LPC.html#PROPOSITIONS.
- POSET::= See http://www.csci.csusb.edu/dick/maths/math_21_Order.html#Posets.
- RELATIONS::= See http://www.csci.csusb.edu/dick/maths/logic_41_HomogenRelations.html
- LichtensteinPnueli00::=following,
[LichtensteinPnueli00].
- Real::= See http://www.csci.csusb.edu/dick/maths/math_42_Numbers.html#Real_Numbers
- Search::= See http://auto.search.msn.com/results.asp?FORM=AS14&v=1&RS=CHECKED&srch=4&q=Modal+logic.
- Sources::= See http://groups.google.com/groups?q=temporal+logic&hl=en&selm=1993Jan27.140803.4254%40city.cs&rnum=1.