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(1)

The Temporal Logic of Knowledge

C ˘at ˘alin Dima

LACL, Universit ´e Paris 12

April 13, 2010

(2)

The muddy children puzzle Logics of knowledge and security

2 The bases

Syntax and semantics Knowledge and time

Types of temporal knowledge Axiomatics and decidability issues

(3)

A puzzle game

n children play together outside,

None wants to get dirty (Dad punishes!), but would like to see the others dirty! (kids...)

It happens that, at some moment, k of them get mud on their foreheads

... so each of them cannot see if he’s dirty or not!

... and none signals anything to anybody who’s dirty!

Mum approaches and says

At least one of you has mud on his forehead Then she asks everybody:

Does anyone of you know whether he’s dirty?

If everybody answers no, she asks againthe same question!

And so on, until someone tells her he/she knows he/she himself/herself is dirty.

Assuming that all children are intelligent, perceptive and truthful (!), what

(4)

A puzzle game

n children play together outside,

None wants to get dirty (Dad punishes!), but would like to see the others dirty! (kids...)

It happens that, at some moment, k of them get mud on their foreheads

... so each of them cannot see if he’s dirty or not!

... and none signals anything to anybody who’s dirty!

Mum approaches and says

At least one of you has mud on his forehead Then she asks everybody:

Does anyone of you know whether he’s dirty?

If everybody answers no, she asks againthe same question!

And so on, until someone tells her he/she knows he/she himself/herself is dirty.

(5)

A puzzle game

n children play together outside,

None wants to get dirty (Dad punishes!), but would like to see the others dirty! (kids...)

It happens that, at some moment, k of them get mud on their foreheads

... so each of them cannot see if he’s dirty or not!

... and none signals anything to anybody who’s dirty!

Mum approaches and says

At least one of you has mud on his forehead Then she asks everybody:

Does anyone of you know whether he’s dirty?

If everybody answers no, she asks againthe same question!

And so on, until someone tells her he/she knows he/she himself/herself is dirty.

Assuming that all children are intelligent, perceptive and truthful (!), what

(6)

A puzzle game

n children play together outside,

None wants to get dirty (Dad punishes!), but would like to see the others dirty! (kids...)

It happens that, at some moment, k of them get mud on their foreheads

... so each of them cannot see if he’s dirty or not!

... and none signals anything to anybody who’s dirty!

Mum approaches and says

At least one of you has mud on his forehead Then she asks everybody:

Does anyone of you know whether he’s dirty?

If everybody answers no, she asks againthe same question!

And so on, until someone tells her he/she knows he/she himself/herself is dirty.

(7)

Let’s be more specific!

When answering, all children provide their answerwithout peeping to the others’ answers!

But each child is aware of the answers of all the others at theprevious steps!

Protocol for answering, avoiding agents getting an advantage if waiting for the others to answer.

So the whole protocol involves Mom’s questions and all the answers at each step.

(8)

Solving the puzzle game

There is a “formal” proof that

the first k−1 times Mum asks her question, all will sayNo, but

the kthtime she asks her question, exactly those children with muddy foreheads will sayYes, I am dirty!

Proof: by induction on k :

For k=1 it’s obvious (ain’t it?).

For k=2, the first time everybody saysNo.

... but then everybody will notice that the two muddy children do not know they are dirty.

Hence muddyaconcludes that, since muddybdoes not deduce that he’s the only one to be dirty, he must have seen mud on someone else’s forehead.

So it must be his (a’s) own forehead that was muddy!

Generalize the reasoning!

(9)

Solving the puzzle game

There is a “formal” proof that

the first k−1 times Mum asks her question, all will sayNo, but

the kthtime she asks her question, exactly those children with muddy foreheads will sayYes, I am dirty!

Proof: by induction on k :

For k=1 it’s obvious (ain’t it?).

For k=2, the first time everybody saysNo.

... but then everybody will notice that the two muddy children do not know they are dirty.

Hence muddyaconcludes that, since muddybdoes not deduce that he’s the only one to be dirty, he must have seen mud on someone else’s forehead.

So it must be his (a’s) own forehead that was muddy!

Generalize the reasoning!

(10)

Solving the puzzle game

There is a “formal” proof that

the first k−1 times Mum asks her question, all will sayNo, but

the kthtime she asks her question, exactly those children with muddy foreheads will sayYes, I am dirty!

Proof: by induction on k :

For k=1 it’s obvious (ain’t it?).

For k=2, the first time everybody saysNo.

... but then everybody will notice that the two muddy children do not know they are dirty.

Hence muddyaconcludes that, since muddybdoes not deduce that he’s the only one to be dirty, he must have seen mud on someone else’s forehead.

So it must be his (a’s) own forehead that was muddy!

Generalize the reasoning!

(11)

Muddy children and knowledge

All children do their reasoning provided theyknowsome properties...

... and deduce (know) later that the othersdo not knowsome other properties.

Mum’s questions serve assynchronization steps.

Without these, there could be no way for children to achieve their deductions!

Step k+1 also represents the convergence of the system tocommon knowledge.

That is,everybody knows that everybody knows that everybody knows that ... that a1. . .ak are dirty

(12)

Why studying logics of knowledge?

Epistemic logics are important inmulti-agent systems.

Originally developed for AI.

Security analysis involves at least two agents: the legitimate user(s) and the intruder(s).

In security protocol analysis, we speak aboutintruder knowledge!

Information flow analysis also is concerned with the information an agent gains about security levels to which he is not authorized to access.

Information is closely related to knowledge.

Formulation of information flow properties in a logic of knowledge.

(13)

What characterizes a logic?

Its syntax.

Its semantics.

Its axiomatic system.

The possibility to “mechanicise” the deduction = decidability of various decision problems.

Various interesting extensions.

(14)

Basic knowledge operators

n agent system – call them 1,2, . . . ,n.

Ki𝜙: agent iknowsformula𝜙.

Examples:

1 n children play their muddy forehead game.

2 p2:child i has mud on his forehead.

3 K4p2:child 4 knows that child 2 is muddy.

4 K1(K4p2p1) :

child 1 knows that child 2 knows that 2 is muddy...

... and also knows that he himself is muddy!

All the other boolean operators:∧,∨,¬,→. . ..

Temporal operators will be added later!

(15)

Basic knowledge operators

n agent system – call them 1,2, . . . ,n.

Ki𝜙: agent iknowsformula𝜙.

Examples:

1 n children play their muddy forehead game.

2 p2:child i has mud on his forehead.

3 K4p2:child 4 knows that child 2 is muddy.

4 K1(K4p2p1) :

child 1 knows that child 2 knows that 2 is muddy...

... and also knows that he himself is muddy!

All the other boolean operators:∧,∨,¬,→. . ..

Temporal operators will be added later!

(16)

Basic knowledge operators

n agent system – call them 1,2, . . . ,n.

Ki𝜙: agent iknowsformula𝜙.

Examples:

1 n children play their muddy forehead game.

2 p2:child i has mud on his forehead.

3 K4p2:child 4 knows that child 2 is muddy.

4 K1(K4p2p1) :

child 1 knows that child 2 knows that 2 is muddy...

... and also knows that he himself is muddy!

All the other boolean operators:∧,∨,¬,→. . ..

Temporal operators will be added later!

(17)

Semantics

Possible worldsmodel:Kripke structurefor n agents:

M = (S,Π, 𝜋,𝒦1, . . . ,𝒦n).

S – the set ofglobal states.

Sometimes S=S1×. . .×Sn.

Si=local statesfor agent i.

Π– set of primitive propositions (like p2:child i is muddy).

𝜋:S→2Π– truth value for each primite propositionin each state.

𝒦i – theindistinguishibility relation(also called the possibility relation).

𝒦i(s,s)= for agent i, states s and scannot be distinguished by prior observation – i.e., according to i’sknowledge!

Very often𝒦iarereflexive, symmetric & transitive– i.e. equivalence relations.

(18)

Semantics (contd.)

Semantics of formulas: evaluated at eachstates:

(M,s)∣=𝜙: formula𝜙holds atstates.

(M,s)∣=p iff p2∈𝜋(s).

(M,s)∣=𝜙1∧𝜙2iff

(M,s)∣=Ki𝜙iff(M,s)∣=𝜙for all swith𝒦i(s,s).

𝜙is a formula that is acquired by i.

All observations bring i to consider that𝜙must hold.

Notation: M ∣=𝜙iff(M,s)∣=𝜙for all sS.

(19)

Semantics (contd.)

Semantics of formulas: evaluated at eachstates:

(M,s)∣=𝜙: formula𝜙holds atstates.

(M,s)∣=p iff p2∈𝜋(s).

(M,s)∣=𝜙1∧𝜙2iff

(M,s)∣=Ki𝜙iff(M,s)∣=𝜙for all swith𝒦i(s,s).

𝜙is a formula that is acquired by i.

All observations bring i to consider that𝜙must hold.

Notation: M ∣=𝜙iff(M,s)∣=𝜙for all sS.

(20)

Semantics (contd.)

Semantics of formulas: evaluated at eachstates:

(M,s)∣=𝜙: formula𝜙holds atstates.

(M,s)∣=p iff p2∈𝜋(s).

(M,s)∣=𝜙1∧𝜙2iff

(M,s)∣=Ki𝜙iff(M,s)∣=𝜙for all swith𝒦i(s,s).

𝜙is a formula that is acquired by i.

All observations bring i to consider that𝜙must hold.

Notation: M ∣=𝜙iff(M,s)∣=𝜙for all sS.

(21)

Semantics (contd.)

Semantics of formulas: evaluated at eachstates:

(M,s)∣=𝜙: formula𝜙holds atstates.

(M,s)∣=p iff p2∈𝜋(s).

(M,s)∣=𝜙1∧𝜙2iff(M,s)∣=𝜙1and(M,s)∣=𝜙2. (M,s)∣=Ki𝜙iff(M,s)∣=𝜙for all swith𝒦i(s,s).

𝜙is a formula that is acquired by i.

All observations bring i to consider that𝜙must hold.

Notation: M ∣=𝜙iff(M,s)∣=𝜙for all sS.

(22)

Muddy children – original situation

Kripke structure Mmud = (S,Π, 𝜋,𝒦i)for n agents.

“Local state” for agent i: Si ={0,1}(muddy or not!).

S=S1×. . .×Sn– that is, 2ninitial situations.

A “global state” is composed of “local states”: s= (s1, . . . ,sn).

Π ={p1, . . . ,pn}.

(Mmud,s)∣=p3iff s3=1.

𝒦i(s,s)iff sj =sjfor all j∕=i.

“Hypercube” representation of Mmud.

What are the states where(Mmud,s)∣=K1p2?

(23)

Muddy children – original situation

Kripke structure Mmud = (S,Π, 𝜋,𝒦i)for n agents.

“Local state” for agent i: Si ={0,1}(muddy or not!).

S=S1×. . .×Sn– that is, 2ninitial situations.

A “global state” is composed of “local states”: s= (s1, . . . ,sn).

Π ={p1, . . . ,pn}.

(Mmud,s)∣=p3iff s3=1.

𝒦i(s,s)iff sj =sjfor all j∕=i.

“Hypercube” representation of Mmud.

What are the states where(Mmud,s)∣=K1p2?

(24)

Other knowledge operators

i considers𝜙possible– Pi𝜙–

(M,s)∣=Pi𝜙iff(M,s)∣=𝜙for some swith𝒦i(s,s).

Everybody in the group G knows𝜙– EG𝜙–

(M,s)∣=EG𝜙iff(M,s)∣=Ki𝜙for all iG.

Distributed knowledge of𝜙within a group: DG𝜙

(M,s)∣=EG𝜙iff(M,s)∣=𝜙for all swith𝒦i(s,s)∀i∈G.

Common knowledge of𝜙within a group G: CG𝜙

(M,s)∣=CG𝜙iff(M,s)∣=EGk𝜙for all k .

That is, each agent knows that each other agent knows that .... knows that𝜙 holds.

Stronger than EGand distributed knowledge!

Which of the following holds in Mmud and in which states?

Pp ,E p ,E p ,D (p ∧p ),C p ,C (p ∧p )?

(25)

Other knowledge operators

i considers𝜙possible– Pi𝜙–

(M,s)∣=Pi𝜙iff(M,s)∣=𝜙for some swith𝒦i(s,s).

Everybody in the group G knows𝜙– EG𝜙–

(M,s)∣=EG𝜙iff(M,s)∣=Ki𝜙for all iG.

Distributed knowledge of𝜙within a group: DG𝜙

(M,s)∣=EG𝜙iff(M,s)∣=𝜙for all swith𝒦i(s,s)∀i∈G.

Common knowledge of𝜙within a group G: CG𝜙

(M,s)∣=CG𝜙iff(M,s)∣=EGk𝜙for all k .

That is, each agent knows that each other agent knows that .... knows that𝜙 holds.

Stronger than EGand distributed knowledge!

Which of the following holds in Mmud and in which states?

P2p2,E1,2p2,E1,2p3,D1,2(p1p2),C1,2p3,C1,2(p1p2)?

(26)

Other knowledge operators

i considers𝜙possible– Pi𝜙–

(M,s)∣=Pi𝜙iff(M,s)∣=𝜙for some swith𝒦i(s,s).

Everybody in the group G knows𝜙– EG𝜙–

(M,s)∣=EG𝜙iff(M,s)∣=Ki𝜙for all iG.

Distributed knowledge of𝜙within a group: DG𝜙

(M,s)∣=EG𝜙iff(M,s)∣=𝜙for all swith𝒦i(s,s)∀i∈G.

Common knowledge of𝜙within a group G: CG𝜙

(M,s)∣=CG𝜙iff(M,s)∣=EGk𝜙for all k .

That is, each agent knows that each other agent knows that .... knows that𝜙 holds.

Stronger than EGand distributed knowledge!

Which of the following holds in Mmud and in which states?

Pp ,E p ,E p ,D (p ∧p ),C p ,C (p ∧p )?

(27)

Other knowledge operators

i considers𝜙possible– Pi𝜙–

(M,s)∣=Pi𝜙iff(M,s)∣=𝜙for some swith𝒦i(s,s).

Everybody in the group G knows𝜙– EG𝜙–

(M,s)∣=EG𝜙iff(M,s)∣=Ki𝜙for all iG.

Distributed knowledge of𝜙within a group: DG𝜙

(M,s)∣=EG𝜙iff(M,s)∣=𝜙for all swith𝒦i(s,s)∀i∈G.

Common knowledge of𝜙within a group G: CG𝜙

(M,s)∣=CG𝜙iff(M,s)∣=EGk𝜙for all k .

That is, each agent knows that each other agent knows that .... knows that𝜙 holds.

Stronger than EGand distributed knowledge!

Which of the following holds in Mmud and in which states?

P2p2,E1,2p2,E1,2p3,D1,2(p1p2),C1,2p3,C1,2(p1p2)?

(28)

Other knowledge operators

i considers𝜙possible– Pi𝜙–

(M,s)∣=Pi𝜙iff(M,s)∣=𝜙for some swith𝒦i(s,s).

Everybody in the group G knows𝜙– EG𝜙–

(M,s)∣=EG𝜙iff(M,s)∣=Ki𝜙for all iG.

Distributed knowledge of𝜙within a group: DG𝜙

(M,s)∣=EG𝜙iff(M,s)∣=𝜙for all swith𝒦i(s,s)∀i∈G.

Common knowledge of𝜙within a group G: CG𝜙

(M,s)∣=CG𝜙iff(M,s)∣=EGk𝜙for all k .

That is, each agent knows that each other agent knows that .... knows that𝜙 holds.

Stronger than EGand distributed knowledge!

Which of the following holds in Mmud and in which states?

Pp ,E p ,E p ,D (p ∧p ),C p ,C (p ∧p )?

(29)

Evolving knowledge

Consider again the muddy children Kripke structure Mmud. What happens when Mum speaks the first time?

Answer:state(0,0, ...,0)disappears!

After Mum’s announcement, it iscommon knowledgethat someone has mud on his forehead!

What happens when Mum speaks the second time?

All states with only one 1 dissapear!

After Mum’s announcement, it iscommon knowledgethatat least two children are dirty!

And so on...

But this is not exactly captured by our system model!

(30)

Evolving knowledge

Consider again the muddy children Kripke structure Mmud. What happens when Mum speaks the first time?

Answer:state(0,0, ...,0)disappears!

After Mum’s announcement, it iscommon knowledgethat someone has mud on his forehead!

What happens when Mum speaks the second time?

All states with only one 1 dissapear!

After Mum’s announcement, it iscommon knowledgethatat least two children are dirty!

And so on...

But this is not exactly captured by our system model!

(31)

Evolving knowledge

Consider again the muddy children Kripke structure Mmud. What happens when Mum speaks the first time?

Answer:state(0,0, ...,0)disappears!

After Mum’s announcement, it iscommon knowledgethat someone has mud on his forehead!

What happens when Mum speaks the second time?

All states with only one 1 dissapear!

After Mum’s announcement, it iscommon knowledgethatat least two children are dirty!

And so on...

But this is not exactly captured by our system model!

(32)

Evolving knowledge

Consider again the muddy children Kripke structure Mmud. What happens when Mum speaks the first time?

Answer:state(0,0, ...,0)disappears!

After Mum’s announcement, it iscommon knowledgethat someone has mud on his forehead!

What happens when Mum speaks the second time?

All states with only one 1 dissapear!

After Mum’s announcement, it iscommon knowledgethatat least two children are dirty!

And so on...

But this is not exactly captured by our system model!

(33)

Evolving knowledge

Consider again the muddy children Kripke structure Mmud. What happens when Mum speaks the first time?

Answer:state(0,0, ...,0)disappears!

After Mum’s announcement, it iscommon knowledgethat someone has mud on his forehead!

What happens when Mum speaks the second time?

All states with only one 1 dissapear!

After Mum’s announcement, it iscommon knowledgethatat least two children are dirty!

And so on...

But this is not exactly captured by our system model!

(34)

Incorporating temporal operators

Future temporal operators:

⃝𝜙– next time𝜙holds.

2𝜙–𝜙holds forever, from now on.

𝜙𝒰𝜓–𝜙holds in every time point until𝜓holds.

3𝜙– there exists a point in the future where𝜙will hold.

And past temporal operators:

𝜙– last time𝜙held.

■𝜙– always before𝜙held.

♦𝜙–𝜙held sometime in the past.

𝜙𝒮𝜓–𝜙held in every time point since𝜓held.

Other operators can be added (e.g. fixpoints).

(35)

Incorporating temporal operators

Future temporal operators:

⃝𝜙– next time𝜙holds.

2𝜙–𝜙holds forever, from now on.

𝜙𝒰𝜓–𝜙holds in every time point until𝜓holds.

3𝜙– there exists a point in the future where𝜙will hold.

And past temporal operators:

𝜙– last time𝜙held.

■𝜙– always before𝜙held.

♦𝜙–𝜙held sometime in the past.

𝜙𝒮𝜓–𝜙held in every time point since𝜓held.

Other operators can be added (e.g. fixpoints).

(36)

Incorporating temporal operators

Future temporal operators:

⃝𝜙– next time𝜙holds.

2𝜙–𝜙holds forever, from now on.

𝜙𝒰𝜓–𝜙holds in every time point until𝜓holds.

3𝜙– there exists a point in the future where𝜙will hold.

And past temporal operators:

𝜙– last time𝜙held.

■𝜙– always before𝜙held.

♦𝜙–𝜙held sometime in the past.

𝜙𝒮𝜓–𝜙held in every time point since𝜓held.

Other operators can be added (e.g. fixpoints).

(37)

Incorporating temporal operators

Future temporal operators:

⃝𝜙– next time𝜙holds.

2𝜙–𝜙holds forever, from now on.

𝜙𝒰𝜓–𝜙holds in every time point until𝜓holds.

3𝜙– there exists a point in the future where𝜙will hold.

And past temporal operators:

𝜙– last time𝜙held.

■𝜙– always before𝜙held.

♦𝜙–𝜙held sometime in the past.

𝜙𝒮𝜓–𝜙held in every time point since𝜓held.

Other operators can be added (e.g. fixpoints).

(38)

Incorporating temporal operators

Future temporal operators:

⃝𝜙– next time𝜙holds.

2𝜙–𝜙holds forever, from now on.

𝜙𝒰𝜓–𝜙holds in every time point until𝜓holds.

3𝜙– there exists a point in the future where𝜙will hold.

And past temporal operators:

𝜙– last time𝜙held.

■𝜙– always before𝜙held.

♦𝜙–𝜙held sometime in the past.

𝜙𝒮𝜓–𝜙held in every time point since𝜓held.

Other operators can be added (e.g. fixpoints).

(39)

Incorporating temporal operators

Future temporal operators:

⃝𝜙– next time𝜙holds.

2𝜙–𝜙holds forever, from now on.

𝜙𝒰𝜓–𝜙holds in every time point until𝜓holds.

3𝜙– there exists a point in the future where𝜙will hold.

And past temporal operators:

𝜙– last time𝜙held.

■𝜙– always before𝜙held.

♦𝜙–𝜙held sometime in the past.

𝜙𝒮𝜓–𝜙held in every time point since𝜓held.

Other operators can be added (e.g. fixpoints).

(40)

Incorporating temporal operators

Future temporal operators:

⃝𝜙– next time𝜙holds.

2𝜙–𝜙holds forever, from now on.

𝜙𝒰𝜓–𝜙holds in every time point until𝜓holds.

3𝜙– there exists a point in the future where𝜙will hold.

And past temporal operators:

𝜙– last time𝜙held.

■𝜙– always before𝜙held.

♦𝜙–𝜙held sometime in the past.

𝜙𝒮𝜓–𝜙held in every time point since𝜓held.

Other operators can be added (e.g. fixpoints).

(41)

Incorporating temporal operators

Future temporal operators:

⃝𝜙– next time𝜙holds.

2𝜙–𝜙holds forever, from now on.

𝜙𝒰𝜓–𝜙holds in every time point until𝜓holds.

3𝜙– there exists a point in the future where𝜙will hold.

And past temporal operators:

𝜙– last time𝜙held.

■𝜙– always before𝜙held.

♦𝜙–𝜙held sometime in the past.

𝜙𝒮𝜓–𝜙held in every time point since𝜓held.

Other operators can be added (e.g. fixpoints).

(42)

Incorporating temporal operators

Future temporal operators:

⃝𝜙– next time𝜙holds.

2𝜙–𝜙holds forever, from now on.

𝜙𝒰𝜓–𝜙holds in every time point until𝜓holds.

3𝜙– there exists a point in the future where𝜙will hold.

And past temporal operators:

𝜙– last time𝜙held.

■𝜙– always before𝜙held.

♦𝜙–𝜙held sometime in the past.

𝜙𝒮𝜓–𝜙held in every time point since𝜓held.

Other operators can be added (e.g. fixpoints).

(43)

Temporal semantics

Transition system for n agents𝒯 = (S,≻):

≻⊆S×S –temporal evolutionof the system.

Runsin𝒯 =infinitesequences of states in S.

Temporal interpreted system over𝒯: ℐ= (Q,Π, 𝜋):

Q=Runs(𝒯)×ℕ–points.

𝜋:Q→2Π– interpretation of propositional symbols.

Semantics of temporal formulas:(ℐ,r,n)∣=𝜙.

(r,n)Q.

(44)

Temporal semantics

Transition system for n agents𝒯 = (S,≻):

≻⊆S×S –temporal evolutionof the system.

Runsin𝒯 =infinitesequences of states in S.

Temporal interpreted system over𝒯: ℐ= (Q,Π, 𝜋):

Q=Runs(𝒯)×ℕ–points.

𝜋:Q→2Π– interpretation of propositional symbols.

Semantics of temporal formulas:(ℐ,r,n)∣=𝜙.

(r,n)Q.

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Temporal semantics

Transition system for n agents𝒯 = (S,≻):

≻⊆S×S –temporal evolutionof the system.

Runsin𝒯 =infinitesequences of states in S.

Temporal interpreted system over𝒯: ℐ= (Q,Π, 𝜋):

Q=Runs(𝒯)×ℕ–points.

𝜋:Q→2Π– interpretation of propositional symbols.

Semantics of temporal formulas:(ℐ,r,n)∣=𝜙.

(r,n)Q.

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Temporal semantics (contd.)

(ℐ,r,n)∣=⃝𝜙iff(ℐ,r,n+1)∣=𝜙.

(ℐ,r,n)∣=2𝜙iff(ℐ,r,m)∣=𝜙forallmn.

(ℐ,r,n)∣=3𝜙iff(ℐ,r,m)∣=𝜙forsomemn.

(ℐ,r,n)∣=𝜙𝒰𝜓iff(ℐ,r,m)∣=𝜓for some mnand(ℐ,r,p)∣=𝜙for all np<m.

(ℐ,r,n)∣= 𝜙iff(ℐ,r,n−1)∣=𝜙(n>0!).

(ℐ,r,n)∣=■𝜙iff(ℐ,r,m)∣=𝜙for all mn.

(ℐ,r,n)∣=♦𝜙iff(ℐ,r,n+1)∣=𝜙for some mn.

(ℐ,r,n)∣=𝜙𝒰𝜓iff(ℐ,r,m)∣=𝜓for some mnand(ℐ,r,p)∣=𝜙for all m<pm.

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Temporal semantics (contd.)

(ℐ,r,n)∣=⃝𝜙iff(ℐ,r,n+1)∣=𝜙.

(ℐ,r,n)∣=2𝜙iff(ℐ,r,m)∣=𝜙forallmn.

(ℐ,r,n)∣=3𝜙iff(ℐ,r,m)∣=𝜙forsomemn.

(ℐ,r,n)∣=𝜙𝒰𝜓iff(ℐ,r,m)∣=𝜓for some mnand(ℐ,r,p)∣=𝜙for all np<m.

(ℐ,r,n)∣= 𝜙iff(ℐ,r,n−1)∣=𝜙(n>0!).

(ℐ,r,n)∣=■𝜙iff(ℐ,r,m)∣=𝜙for all mn.

(ℐ,r,n)∣=♦𝜙iff(ℐ,r,n+1)∣=𝜙for some mn.

(ℐ,r,n)∣=𝜙𝒰𝜓iff(ℐ,r,m)∣=𝜓for some mnand(ℐ,r,p)∣=𝜙for all m<pm.

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Muddy children example

Transition system:𝒯 = (S,≻)with≻={(s,s)sS}.

Local states are unchanged during the run!

Run – identified with the (unique) state occurring in it!

Hence points = pairs (state, timepoint).

Interpretation:𝜋(s,n) ={pisi =1}.

Possibility relations:

𝒦i(

(s,k),(s.k))

iff s=sor supp(s),supp(s)≥k and sj =sj∀j∕=i

supp(s) ={i∣si =1}.

Draw it!

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Temporal knowledge properties of the muddy children

(s,1)∣=C(p1∨. . .∨pn)iff . In general,(s,k)∣=C .

If(s,k)∣=Pipi then(s,k+1)∣=C(PipiPi¬pi).

If supp(s) =k then for each i with si =1 we have(s,k)∣=Kipi.

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Temporal knowledge properties of the muddy children

(s,1)∣=C(p1∨. . .∨pn)iff s∕= (0, . . . ,0).

In general,(s,k)∣=C .

If(s,k)∣=Pipi then(s,k+1)∣=C(PipiPi¬pi).

If supp(s) =k then for each i with si =1 we have(s,k)∣=Kipi.

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Temporal knowledge properties of the muddy children

(s,1)∣=C(p1∨. . .∨pn)iff s∕= (0, . . . ,0).

In general,(s,k)∣=C

∣S∣≥k

j∈S

pi.

If(s,k)∣=Pipi then(s,k+1)∣=C(PipiPi¬pi).

If supp(s) =k then for each i with si =1 we have(s,k)∣=Kipi.

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Synchronicity

Agents have access to a shared clock.

For the muddy children, it is Mum’s announcements that play the role of a clock.

The system issynchronous.

SynchronousKripke structure over a transition system𝒯: M = (ℐ,𝒦1, . . . ,𝒦n):

If𝒦i

((r,n),(r,n))

then n=n.

The points that i considers possible at(r,n)are those whose clock is n too.

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Perfect recall

With the general definition of𝒦i, agent i’s knowledge may vary during system evolution.

We would like it to be onlycumulative

What i learned at a point(r,n)has to be “preserved” at later points(r,n) (nn).

Kripke structure withperfect recall: M= (ℐ,𝒦1, . . . ,𝒦n):

Local state sequence at(r,n): sequence of si,without repetitions.

E.g. if i’s local states at instants 0. . .4 are(si,si,si,si,si), then lss(r,4) = (si,si,si).

Perfect recall: equivalent points only if local state sequence is the same:

If𝒦i

((r,n),(r,n))

then lss(r,n) =lss(r,n)

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Synchrony & perfect recall

Perfect recall does not mean Ki𝜙→2Ki𝜙!

Example: muddy children with𝜙=PipiPi¬pi. Dual notion: no learning:

Speaks about future local state sequence.

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Synchrony & perfect recall

Perfect recall does not mean Ki𝜙→2Ki𝜙!

Example: muddy children with𝜙=PipiPi¬pi. Dual notion: no learning:

Speaks about future local state sequence.

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Axioms for knowledge without time

Pr Axioms and rules for the propositional operators.

K. Distribution axiom:(Ki𝜙∧Ki(𝜙→𝜓)→Ki𝜓 T. Knowledge axiom: Ki𝜙→𝜙

4. Positive introspection axiom: Ki𝜙→KiKi𝜙 5. Negative introspection axiom:¬KiKi¬Ki𝜙

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Axioms for knowledge without time

Pr Axioms and rules for the propositional operators.

K. Distribution axiom:(Ki𝜙∧Ki(𝜙→𝜓)→Ki𝜓 T. Knowledge axiom: Ki𝜙→𝜙

4. Positive introspection axiom: Ki𝜙→KiKi𝜙 5. Negative introspection axiom:¬KiKi¬Ki𝜙

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Correctness and completeness

Knowledge generalization rule:

If M∣=𝜙then M∣=Ki𝜙 The whole = systemS5n.

Theorem

For any structure M in which each possibility relation𝒦i is anequivalence, and all agents i, the above axioms and rule hold.

Theorem

S5nis a sound and complete axiomatization of the logic of knowledge in

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Correctness and completeness

Knowledge generalization rule:

If M∣=𝜙then M∣=Ki𝜙 The whole = systemS5n.

Theorem

For any structure M in which each possibility relation𝒦i is anequivalence, and all agents i, the above axioms and rule hold.

Theorem

S5nis a sound and complete axiomatization of the logic of knowledge in which𝒦i are all equivalence relations.

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Common knowledge and distributed knowledge

1 Defining axiom for “everibody knows”: EG𝜙→⋀

i∈GKi𝜙

2 Fixpoint axiom for common knowledge: CG𝜙↔EG(𝜙∧CG𝜙)

3 Induction rule for common knowledge:

If M∣=EG(𝜙∧CG𝜙)then M∣=CG𝜙

4 Subgroup axioms: EG𝜙→EH𝜙for all HG.

5 Similarly for CGand DG.

6 System S5Cn – correct and complete.

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Axiomatizing time

2and3can be expressed in terms of𝒰

How?

Axioms for⃝and𝒰:

Distributivity:⃝𝜙∧ ⃝(𝜙→𝜓)→ ⃝𝜓.

Linear time:¬ ⃝𝜙↔ ⃝¬𝜙.

Fixpoint axiom for until:𝜙𝒰𝜓↔𝜓∨(𝜙∧ ⃝(𝜙𝒰𝜓)).

Next time rule: from𝜙infer2𝜙.

Until inference rule: from𝜙→ ¬𝜓∧ ⃝𝜙infer𝜙→ ¬(𝜙𝒰𝜓).

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Axiomatizing time

2and3can be expressed in terms of𝒰

How?

Axioms for⃝and𝒰:

Distributivity:⃝𝜙∧ ⃝(𝜙→𝜓)→ ⃝𝜓.

Linear time:¬ ⃝𝜙↔ ⃝¬𝜙.

Fixpoint axiom for until:𝜙𝒰𝜓↔𝜓∨(𝜙∧ ⃝(𝜙𝒰𝜓)).

Next time rule: from𝜙infer2𝜙.

Until inference rule: from𝜙→ ¬𝜓∧ ⃝𝜙infer𝜙→ ¬(𝜙𝒰𝜓).

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Combining time and knowledge axiomatically

General systems:no additional axioms!

Knowledge and time areindependent in general!

Perfect recall:they do interact

(KT 1) Ki2𝜙→2Ki𝜙

Formulas known to be always true must always be known to be true (!) Synchrony & perfect recall: stronger interaction

(KT 2) Ki⃝𝜙→ ⃝Ki𝜙

Theorem

S5Un +KT 2 is a sound and complete axiomatization for synchrony and perfect

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Combining time and knowledge axiomatically

General systems:no additional axioms!

Knowledge and time areindependent in general!

Perfect recall:they do interact

(KT 1) Ki2𝜙→2Ki𝜙

Formulas known to be always true must always be known to be true (!) Synchrony & perfect recall: stronger interaction

(KT 2) Ki⃝𝜙→ ⃝Ki𝜙

Theorem

S5U+KT 2 is a sound and complete axiomatization for synchrony and perfect

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Satisfiability – pure knowledge case

Theorem

The satisfiability problem for S5nis PSPACE-complete – and thus, the validity problem for S5nis co-PSPACE-complete.

The satisfiability problem for S5Cn is EXPTIME-complete – and thus the validity problem for S5Cn is co-EXPTIME-complete.

Based on theorems on the existence of finite models.

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Model checking

Basic case – no common knowledge, no time:

Theorem

There is an algorithm that, given a Kripke structure M, a state s and a formula 𝜙, determines in time O(∣M∣ × ∣𝜙∣), whether(M,s)∣=𝜙.

Common knowledge, no until:

Theorem

The model checking problem for synchronous perfect recall systems and the temporal logic with common knowledge but without until isPSPACE-complete.

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Model checking

Until, no common knowledge:

Theorem

The model checking problem for synchronous perfect recall systems and the temporal logic of knowledge with until but without common knowledge is decidable innonelementary time.

Full (future) temporal logic and knowledge operators:

Theorem

The model checking problem for synchronous perfect recall systems and the temporal logic of knowledge with until and common knowledge isundecidable.

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