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(1)

Non-uniform Hypercoherences

Pierre Boudes

Institut de Math´ematiques de Luminy

(2)

What’s this talk about?

Denotational semantics (of λ-calculus, PCF, LL) proofs, terms → some math. structures: agents

sequentiality & determinism. No concurrency Internal interactivity of calculus

extensionality (PER), extensional collapse (quotient) uniformity: the stage where agents interact

Exponential modalities of linear logic (! and ?) resource management

complexity issue (ELL, LLL), polarities, . . .

(3)

What’s this talk about?

Denotational semantics (of λ-calculus, PCF, LL)

proofs, terms → some math. structures: agents sequentiality & determinism. No concurrency

Internal interactivity of calculus

extensionality (PER), extensional collapse (quotient) uniformity: the stage where agents interact

Exponential modalities of linear logic (! and ?) resource management

complexity issue (ELL, LLL), polarities, . . .

(4)

What’s this talk about?

Denotational semantics (of λ-calculus, PCF, LL)

proofs, terms → some math. structures: agents sequentiality & determinism. No concurrency

Internal interactivity of calculus

extensionality (PER), extensional collapse (quotient) uniformity: the stage where agents interact

Exponential modalities of linear logic (! and ?) resource management

complexity issue (ELL, LLL), polarities, . . .

(5)

What’s this talk about?

Denotational semantics (of λ-calculus, PCF, LL)

proofs, terms → some math. structures: agents sequentiality & determinism. No concurrency

Internal interactivity of calculus extensionality (PER), extensional collapse (quotient)

uniformity: the stage where agents interact Exponential modalities of linear logic (! and ?)

resource management

complexity issue (ELL, LLL), polarities, . . .

(6)

What’s this talk about?

Denotational semantics (of λ-calculus, PCF, LL)

proofs, terms → some math. structures: agents sequentiality & determinism. No concurrency

Internal interactivity of calculus

extensionality (PER), extensional collapse (quotient) uniformity: the stage where agents interact

Exponential modalities of linear logic (! and ?) resource management

complexity issue (ELL, LLL), polarities, . . .

(7)

What’s this talk about?

Denotational semantics (of λ-calculus, PCF, LL)

proofs, terms → some math. structures: agents sequentiality & determinism. No concurrency

Internal interactivity of calculus

extensionality (PER), extensional collapse (quotient) uniformity: the stage where agents interact

Exponential modalities of linear logic (! and ?) resource management

complexity issue (ELL, LLL), polarities, . . .

(8)

What’s this talk about?

Denotational semantics (of λ-calculus, PCF, LL)

proofs, terms → some math. structures: agents sequentiality & determinism. No concurrency

Internal interactivity of calculus

extensionality (PER), extensional collapse (quotient) uniformity: the stage where agents interact

Exponential modalities of linear logic (! and ?) resource management

complexity issue (ELL, LLL), polarities, . . .

(9)

What’s this talk about?

Denotational semantics (of λ-calculus, PCF, LL)

proofs, terms → some math. structures: agents sequentiality & determinism. No concurrency

Internal interactivity of calculus

extensionality (PER), extensional collapse (quotient) uniformity: the stage where agents interact

Exponential modalities of linear logic (! and ?) resource management

complexity issue (ELL, LLL), polarities, . . .

(10)

What’s this talk about?

Denotational semantics (of λ-calculus, PCF, LL)

proofs, terms → some math. structures: agents sequentiality & determinism. No concurrency

Internal interactivity of calculus

extensionality (PER), extensional collapse (quotient) uniformity: the stage where agents interact

Exponential modalities of linear logic (! and ?) resource management

complexity issue (ELL, LLL), polarities, . . .

(11)

Uniformity at a first sight

P = λb. if b then { if b then t1 else t2 } else { if b then t3 else t4 } P:Bool → Bool ∼= !Bool Bool

ti ∈ {t, f}

(12)

Uniformity at a first sight

P = λb. if b then { if b then t1 else t2 } else { if b then t3 else t4 } P:Bool → Bool ∼= !Bool Bool

ti ∈ {t, f}

(13)

Uniformity at a first sight

P = λb. if b then { if b then t1 else t2 } else { if b then t3 else t4 } P:Bool → Bool ∼= !Bool Bool

ti ∈ {t, f}

(14)

Uniformity at a first sight

P = λb. if b then { if b then t1 else t2 } else { if b then t3 else t4 } P:Bool → Bool ∼= !Bool Bool

ti ∈ {t, f}

(15)

Uniformity at a first sight

P = λb. if b then { if b then t1 else t2 } else { if b then t3 else t4 } P:Bool → Bool ∼= !Bool Bool

ti ∈ {t, f}

Coherence spaces and hypercoherences semantics (set-based) are uniform

P = {({t}, t ), ({f}, t )}

(16)

Uniformity at a first sight

P = λb. if b then { if b then t1 else t2 } else { if b then t3 else t4 } P:Bool → Bool ∼= !Bool Bool

ti ∈ {t, f}

Relational semantics is non-uniform

P = {([t, t], t1), ([t, f], t2), ([t, f], t3), ([f, f], t4)}

(17)

Uniformity at a first sight

P = λb. if b then { if b then t1 else t2 } else { if b then t3 else t4 } P:Bool → Bool ∼= !Bool Bool

ti ∈ {t, f}

Multiset-based coherence spaces and

hypercoherences semantics are also uniform P = {([t, t], t ), ([f, f], t )}

(18)

Denotational semantics

Static semantics : Agents are sets of points

additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

|A B| = |A B| = |A ⊗ B| = |A| × |B|

Dynamic semantics : Agents are sets of pol. paths

additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

(19)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

|A B| = |A B| = |A ⊗ B| = |A| × |B|

Dynamic semantics : Agents are sets of pol. paths

additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

(20)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

|A B| = |A B| = |A ⊗ B| = |A| × |B|

Dynamic semantics: Agents are sets of pol. paths additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

(21)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

|A B| = |A B| = |A ⊗ B| = |A| × |B|

Dynamic semantics: Agents are sets of pol. paths additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

(22)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

|A B| = |A B| = |A ⊗ B| = |A| × |B|

Dynamic semantics: Agents are sets of pol. paths additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

(23)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

|A B| = |A B| = |A ⊗ B| = |A| × |B|

Dynamic semantics: Agents are sets of pol. paths additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

(24)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

exponentials → finite sets or multisets , agents

Dynamic semantics: Agents are sets of pol. paths additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

(25)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

exponentials → finite sets or multisets, agents Dynamic semantics: Agents are sets of pol. paths

additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

(26)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

exponentials → finite sets or multisets, agents Dynamic semantics: Agents are sets of pol. paths

additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths

in agents

(27)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

exponentials → finite sets or multisets, agents Dynamic semantics: Agents are sets of pol. paths

additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

(28)

Denotational semantics

Static semantics: Agents are sets of points additives → disjoint unions, ∅

multiplicatives → product of sets, {∗}

exponentials → finite sets or multisets, agents Dynamic semantics: Agents are sets of pol. paths

additives → disjoint unions, ∅

multiplicatives→ interleaving of paths, {ε}, {∗O}, {∗P} exponentials → interleaving of paths in agents

uniformity

(29)

Denotational semantics

Static semantics bridge?

Dynamic semantics

(30)

Denotational semantics

Static semantics Hypercoh.

bridge? Ext. Coll. EHRHARD [Ehr96]

Dynamic semantics Seq. Alg.

(31)

Denotational semantics

Static semantics Hypercoh.

bridge?

Dynamic semantics Seq. Alg.

PER ∼. Equality on basis types and :

f ∼A→B g iff x ∼A y =⇒ f(x) ∼B f(y) (∀x, y)

(32)

Denotational semantics

Static semantics Hypercoh.

bridge?

Dynamic semantics Seq. Alg.

one-way bridge abstract result

Only simple types. Not the full power of linear logic.

(33)

Denotational semantics

Static semantics Hypercoh.

bridge?

Dynamic semantics Seq. Alg.

one-way bridge abstract result Only simple types. Not the full power of linear logic.

(34)

Denotational semantics

Static semantics Hypercoh.

bridge?

Dynamic semantics Seq. Alg.

one-way bridge abstract result

Only simple types. Not the full power of linear logic.

(35)

Denotational semantics

Static semantics Hypercoh.

bridge?

Dynamic semantics Seq. Alg. HO non-unif.

LAIRD [Lai01]

(36)

Denotational semantics

Static semantics Hypercoh. non-unif.

bridge?

Dynamic semantics Seq. Alg. HO non-unif.

Shifting to non-uniformity might improve the bridge

(37)

Denotational semantics

Static semantics Hypercoh. non-unif.

bridge?

Dynamic semantics Seq. Alg. HO non-unif.

Shifting to non-uniformity might improve the bridge

(38)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|)

Hypercoherence X = (|X|, ^_X): hypergraph {{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|)

Reflexivity

(39)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|)

Reflexivity

(40)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|) Reflexivity

(41)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|) Reflexivity

Powers

A Power P is a functor from the category of sets and

(42)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|) Reflexivity

A Power P is a functor from the category of sets and inclusions to itself.

(43)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|) Reflexivity : ∪a∈|X|P ({a}) ⊆ ^_X

A Power P is a functor from the category of sets and

(44)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|) Reflexivity : ∪a∈|X|P ({a}) ⊆ ^_X

Orthogonal : X

|X| = |X| and ^_ = _^

(45)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|) Reflexivity : ∪a∈|X|P ({a}) ⊆ ^_X ^_

Orthogonal : X

(46)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|)

Reflexivity : ∪a∈|X|P ({a}) ⊆ ^_X ^_ _^

P (|X|) Orthogonal : X

|X| = |X| and ^_ = _^

(47)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|)

Reflexivity : ∪a∈|X|P ({a}) ⊆ ^_X ^_ _^

P (|X|)

^

_ Orthogonal : X

(48)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|)

Reflexivity : ∪a∈|X|P ({a}) ⊆ ^_X ^_ _^

P (|X|)

^

_ Agent x ⊆ |X|, P (x) ⊆ ^_X

Counter-agent y ⊆ |X|, P (y) ⊆ _^X Determinism ](x ∩ y) ≤ 1

(49)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|)

Reflexivity : ∪a∈|X|P ({a}) ⊆ ^_X ^_ _^

P (|X|)

^

_ Agent x ⊆ |X|, P (x) ⊆ ^_X

Determinism ](x ∩ y) ≤ 1

(50)

Uniform spaces

Coherence space X = (|X|, ^_X): graph

{[a, a] | a ∈ |X|} ⊆ ^_X ⊆ M{2}(|X|) Hypercoherence X = (|X|, ^_X): hypergraph

{{a} | a ∈ |X|} ⊆ ^_X ⊆ Pfin (|X|)

Reflexivity : ∪a∈|X|P ({a}) ⊆ ^_X ^_ _^

P (|X|)

^

_ Agent x ⊆ |X|, P (x) ⊆ ^_X

Counter-agent y ⊆ |X|, P (y) ⊆ _^X

(51)

Non-uniform spaces

P -coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

(52)

Non-uniform spaces

P -coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^ No longer reflexive. Neutrality. _

(53)

Non-uniform spaces

P -coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^ No longer reflexive. Neutrality. _

eg, for the power M{2}, one can have both a ^_ b and a _^ b with a 6= b and also c _ c, d ^ d.

(54)

Non-uniform spaces

P -coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^ No longer reflexive. Neutrality. _

eg, for the power M{2}, one can have both a ^_ b and a _^ b with a 6= b and also c _ c, d ^ d.

In [BE01], BUCCIARELLI & EHRHARD have set a general framework where each phase-valued provability seman- tics of an indexed linear logic gives a non-uniform deno- tational semantics of linear logic.

(55)

Non-uniform spaces

P -coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^ No longer reflexive. Neutrality. _

eg, for the power M{2}, one can have both a ^_ b and a _^ b with a 6= b and also c _ c, d ^ d.

In [BE01], BUCCIARELLI & EHRHARD have set a general framework where each phase-valued provability seman- tics of an indexed linear logic gives a non-uniform deno- tational semantics of linear logic.

→ a class of non-uniform coherence semantics which

(56)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

(57)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

MALL model: standard pattern

(58)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

MALL model: standard pattern

eg, |X Y | = |X| × |Y | and, for s ∈ MK(|X Y |):

s ∈ ^_X Y iff

1(s) ∈ ^_X =⇒ π2(s) ∈ ^_Y π1(s) ∈ _^X ⇐= π2(s) ∈ _^Y s ∈ N iff π (s) ∈ N and π (s) ∈ N

(59)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

MALL model: standard pattern for MALL neutrality is reflexivity

(60)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

MALL model: standard pattern for MALL neutrality is reflexivity exponentials are responsible for neutrality6=reflexivity

(61)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

MALL model: standard pattern for MALL neutrality is reflexivity exponentials are responsible for neutrality6=reflexivity

the exponentials badly behaved:

no determinism

no related uniform semantics

for M \{0,1}, non sequential ag. (som. like // or)

(62)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

MALL model: standard pattern for MALL neutrality is reflexivity exponentials are responsible for neutrality6=reflexivity

the exponentials badly behaved:

no determinism no related uniform semantics

for M \{0,1}, non sequential ag. (som. like // or)

(63)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

MALL model: standard pattern for MALL neutrality is reflexivity exponentials are responsible for neutrality6=reflexivity

the exponentials badly behaved:

no determinism

no related uniform semantics for M \{0,1}, non sequential ag. (som. like // or)

(64)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

MALL model: standard pattern for MALL neutrality is reflexivity exponentials are responsible for neutrality6=reflexivity

the exponentials badly behaved:

no determinism

no related uniform semantics

for M \{0,1}, non sequential ag. (som. like // or)

(65)

Non-uniform spaces

MK-coherence space (|X|, ^_X, _^X) ^_ _^

P (|X|) NX

^

_

MALL model: standard pattern for MALL neutrality is reflexivity exponentials are responsible for neutrality6=reflexivity

the exponentials badly behaved:

no determinism

no related uniform semantics

(66)

The exponentials

Web: |!X| = Mfin(|X|)

Coherence. For each [xi | i ∈ I] ∈ MK(|!X|) we set:

[xi | i ∈ I] ∈ ^!X iff ∃[ai | i ∈ I] ∈ ^X, ∀i ∈ I, ai ∈ xi [xi | i ∈ I] ∈ N!X iff [xi | i ∈ I] ∈/ ^!X and ∃(aji)j∈Ji∈I ,

∀i ∈ I, [aji | j ∈ J] = xi and

∀j ∈ J, [aji | i ∈ I] ∈ NX

(67)

The exponentials

Web: |!X| = Mfin(|X|) Coherence. For each [xi | i ∈ I] ∈ MK(|!X|) we set:

[xi | i ∈ I] ∈ ^!X iff ∃[ai | i ∈ I] ∈ ^X, ∀i ∈ I, ai ∈ xi [xi | i ∈ I] ∈ N!X iff [xi | i ∈ I] ∈/ ^!X and ∃(aji)j∈Ji∈I ,

∀i ∈ I, [aji | j ∈ J] = xi and

∀j ∈ J, [aji | i ∈ I] ∈ NX

(68)

The exponentials

Web: |!X| = Mfin(|X|)

This web is the same as for relational model, so the semantics is non-uniform. A uniform web would have been {x ∈ Mfin(|X|) | supp(x) ∈ agent(X)}.

Coherence. For each [xi | i ∈ I] ∈ MK(|!X|) we set:

[xi | i ∈ I] ∈ ^!X iff ∃[ai | i ∈ I] ∈ ^X, ∀i ∈ I, ai ∈ xi [xi | i ∈ I] ∈ N!X iff [xi | i ∈ I] ∈/ ^!X and ∃(aji)ji∈IJ,

∀i ∈ I, [aji | j ∈ J] = xi and

∀j ∈ J, [aji | i ∈ I] ∈ NX

(69)

The exponentials

Web: |!X| = Mfin(|X|)

Coherence. For each [xi | i ∈ I] ∈ MK(|!X|) we set:

[xi | i ∈ I] ∈ ^!X iff ∃[ai | i ∈ I] ∈ ^X, ∀i ∈ I, ai ∈ xi [xi | i ∈ I] ∈ N!X iff [xi | i ∈ I] ∈/ ^!X and ∃(aji)j∈Ji∈I ,

∀i ∈ I, [aji | j ∈ J] = xi and

∀j ∈ J, [aji | i ∈ I] ∈ NX

(70)

The exponentials

Web: |!X| = Mfin(|X|)

Coherence. For each [xi | i ∈ I] ∈ MK(|!X|) we set:

[xi | i ∈ I] ∈ ^!X iff ∃[ai | i ∈ I] ∈ ^X, ∀i ∈ I, ai ∈ xi [xi | i ∈ I] ∈ N!X iff [xi | i ∈ I] ∈/ ^!X and ∃(aji)ji∈I∈J,

∀i ∈ I, [aji | j ∈ J] = xi and

∀j ∈ J, [aji | i ∈ I] ∈ NX

x1 x2 x...n

(71)

The exponentials

Web: |!X| = Mfin(|X|)

Coherence. For each [xi | i ∈ I] ∈ MK(|!X|) we set:

[xi | i ∈ I] ∈ ^!X iff ∃[ai | i ∈ I] ∈ ^X, ∀i ∈ I, ai ∈ xi [xi | i ∈ I] ∈ N!X iff [xi | i ∈ I] ∈/ ^!X and ∃(aji)ji∈I∈J,

∀i ∈ I, [aji | j ∈ J] = xi and

∀j ∈ J, [aji | i ∈ I] ∈ NX

x1 x2 x...n

a1 a2 an

(72)

The exponentials

Web: |!X| = Mfin(|X|)

Coherence. For each [xi | i ∈ I] ∈ MK(|!X|) we set:

[xi | i ∈ I] ∈ ^!X iff ∃[ai | i ∈ I] ∈ ^X, ∀i ∈ I, ai ∈ xi [xi | i ∈ I] ∈ N!X iff [xi | i ∈ I] ∈/ ^!X and ∃(aji)ji∈IJ,

∀i ∈ I, [aji | j ∈ J] = xi and

∀j ∈ J, [aji | i ∈ I] ∈ NX

(73)

The exponentials

Web: |!X| = Mfin(|X|)

Coherence. For each [xi | i ∈ I] ∈ MK(|!X|) we set:

[xi | i ∈ I] ∈ ^!X iff ∃[ai | i ∈ I] ∈ ^X, ∀i ∈ I, ai ∈ xi [xi | i ∈ I] ∈ N!X iff [xi | i ∈ I] ∈/ ^!X and ∃(aji)ji∈IJ,

∀i ∈ I, [aji | j ∈ J] = xi and

∀j ∈ J, [aji | i ∈ I] ∈ NX

x1 x2

...

(74)

The exponentials

Web: |!X| = Mfin(|X|)

Coherence. For each [xi | i ∈ I] ∈ MK(|!X|) we set:

[xi | i ∈ I] ∈ ^!X iff ∃[ai | i ∈ I] ∈ ^X, ∀i ∈ I, ai ∈ xi [xi | i ∈ I] ∈ N!X iff [xi | i ∈ I] ∈/ ^!X and ∃(aji)ji∈IJ,

∀i ∈ I, [aji | j ∈ J] = xi and

∀j ∈ J, [aji | i ∈ I] ∈ NX x1 x2 x...n

(75)

Properties

Non-uniform model of linear logic (logical forgetful functor).

Co-free ⊗-comonoid. (so maximality).

Determinism: NX ⊆ ∪a∈|X|MK({a}) Stage of interaction: neutral web

|X|N,K = {a ∈ |X| | MK({a}) ⊆ NX} and functor NK of restriction to the neutral web.

|!X|N,K = {x ∈ Mfin(|X|N,K) | supp(x) ∈ agent(X)}

u! = NK!. A new class of uniform models related to the non-uniform ones in a very comfortable way.

(76)

Properties

Non-uniform model of linear logic (logical forgetful functor).

Co-free ⊗-comonoid. (so maximality).

Determinism: NX ⊆ ∪a∈|X|MK({a}) Stage of interaction: neutral web

|X|N,K = {a ∈ |X| | MK({a}) ⊆ NX} and functor NK of restriction to the neutral web.

|!X|N,K = {x ∈ Mfin(|X|N,K) | supp(x) ∈ agent(X)}

u! = NK!. A new class of uniform models related to the non-uniform ones in a very comfortable way.

(77)

Properties

Non-uniform model of linear logic (logical forgetful functor).

Co-free ⊗-comonoid. (so maximality).

Determinism: NX ⊆ ∪a∈|X|MK({a}) Stage of interaction: neutral web

|X|N,K = {a ∈ |X| | MK({a}) ⊆ NX} and functor NK of restriction to the neutral web.

|!X|N,K = {x ∈ Mfin(|X|N,K) | supp(x) ∈ agent(X)}

u! = NK!. A new class of uniform models related to the non-uniform ones in a very comfortable way.

(78)

Properties

Non-uniform model of linear logic (logical forgetful functor).

Co-free ⊗-comonoid. (so maximality).

Determinism: NX ⊆ ∪a∈|X|MK({a}) Stage of interaction: neutral web

|X|N,K = {a ∈ |X| | MK({a}) ⊆ NX} and functor NK of restriction to the neutral web.

|!X|N,K = {x ∈ Mfin(|X|N,K) | supp(x) ∈ agent(X)}

u! = NK!. A new class of uniform models related to the non-uniform ones in a very comfortable way.

(79)

Properties

Non-uniform model of linear logic (logical forgetful functor).

Co-free ⊗-comonoid. (so maximality).

Determinism: NX ⊆ ∪a∈|X|MK({a}) Stage of interaction: neutral web

|X|N,K = {a ∈ |X| | MK({a}) ⊆ NX} and functor NK of restriction to the neutral web.

|!X|N,K = {x ∈ Mfin(|X|N,K) | supp(x) ∈ agent(X)}

u! = NK!. A new class of uniform models related to the non-uniform ones in a very comfortable way.

(80)

Properties

Non-uniform model of linear logic (logical forgetful functor).

Co-free ⊗-comonoid. (so maximality).

Determinism: NX ⊆ ∪a∈|X|MK({a}) Stage of interaction: neutral web

|X|N,K = {a ∈ |X| | MK({a}) ⊆ NX} and functor NK of restriction to the neutral web.

|!X|N,K = {x ∈ Mfin(|X|N,K) | supp(x) ∈ agent(X)}

u! = NK!. A new class of uniform models related to the non-uniform ones in a very comfortable way.

(81)

Properties

Non-uniform model of linear logic (logical forgetful functor).

Co-free ⊗-comonoid. (so maximality).

Determinism: NX ⊆ ∪a∈|X|MK({a}) Stage of interaction: neutral web

|X|N,K = {a ∈ |X| | MK({a}) ⊆ NX} and functor NK of restriction to the neutral web.

|!X|N,K = {x ∈ Mfin(|X|N,K) | supp(x) ∈ agent(X)}

!. A new class of uniform models related

(82)

Semantics

[π]M

K = [π]R and for the related uniform semantics : [π]u,M

K = NK([π]R).

K = {2} → coherence spaces. [π]COH = N{2}([π]R) K = \{0, 1} → multicoherences. Generalize

hypercoherences to multiplicities aware coherence relations.

Forget multiplicities → non-unif. hypercoherences ( !

nuh = S!). Usual (multiset-based) uniform semantics. !

mh = N !

nuh.

(83)

Semantics

[π]M

K = [π]R and for the related uniform semantics : [π]u,M

K = NK([π]R).

K = {2} → coherence spaces. [π]COH = N{2}([π]R) K = \{0, 1} → multicoherences. Generalize

hypercoherences to multiplicities aware coherence relations.

Forget multiplicities → non-unif. hypercoherences ( !

nuh = S!). Usual (multiset-based) uniform semantics. !

mh = N !

nuh.

(84)

Semantics

[π]M

K = [π]R and for the related uniform semantics : [π]u,M

K = NK([π]R).

K = {2} → coherence spaces. [π]COH = N{2}([π]R) K = \{0, 1} → multicoherences. Generalize

hypercoherences to multiplicities aware coherence relations.

Forget multiplicities → non-unif. hypercoherences ( !

nuh = S!). Usual (multiset-based) uniform semantics. !

mh = N !

nuh.

(85)

Semantics

[π]M

K = [π]R and for the related uniform semantics : [π]u,M

K = NK([π]R).

K = {2} → coherence spaces. [π]COH = N{2}([π]R) K = \{0, 1} → multicoherences. Generalize

hypercoherences to multiplicities aware coherence relations.

Forget multiplicities → non-unif. hypercoherences ( !

nuh = S!). Usual (multiset-based) uniform semantics. !

mh = N !

nuh.

(86)

Semantics

[π]M

K = [π]R and for the related uniform semantics : [π]u,M

K = NK([π]R).

K = {2} → coherence spaces. [π]COH = N{2}([π]R) K = \{0, 1} → multicoherences. Generalize

hypercoherences to multiplicities aware coherence relations.

Forget multiplicities → non-unif. hypercoherences ( !

nuh = S!). Usual (multiset-based) uniform semantics. !

mh = N !

nuh.

(87)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model

Extensional collapses (using a MELLIÈS result, [Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(88)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model

Extensional collapses (using a MELLIÈS result, [Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(89)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model Extensional collapses (using a MELLIÈS result,

[Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(90)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model

Extensional collapses (using a MELLIÈS result, [Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(91)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model

Extensional collapses (using a MELLIÈS result, [Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(92)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model

Extensional collapses (using a MELLIÈS result, [Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(93)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model

Extensional collapses (using a MELLIÈS result, [Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(94)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model

Extensional collapses (using a MELLIÈS result, [Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(95)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model

Extensional collapses (using a MELLIÈS result, [Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(96)

Extensionality

Multiset-based models aren’t extensional There is no set based non-uniform model

Extensional collapses (using a MELLIÈS result, [Mel01]):

m.-based coh. sp./ ∼ = s.-based coh. sp.

m.-based hypercoh./ ∼ = s.-based hypercoh.

non-unif.MK-coh./ ∼ = unif. MK-coh./ ∼ non-unif. coh. sp./ ∼ = s.-based coh. sp.

→ s.-based multicoherences (direct description).

non-unif. hypercoh./ ∼ = s.-based hypercoh.

(97)

Sequentiality

Non-uniform semantics : non-sequential, eg, {([t], t), ([f], t), ([t, f], t)}

is an agent of type !Bool Bool.

Multicoherence semantics: sequentiality at first order. Every finite agent of type

!(Bool & . . . & Bool) Bool is definable in PCF. Multicoherences 6= hypercoherences → two

(extensionally) different notions of higher order

sequentiality. (Contrarily to what was expected, eg in [Lon02]).

(98)

Sequentiality

Non-uniform semantics : non-sequential, eg, {([t], t), ([f], t), ([t, f], t)}

is an agent of type !Bool Bool.

Multicoherence semantics: sequentiality at first order. Every finite agent of type

!(Bool & . . . & Bool) Bool is definable in PCF. Multicoherences 6= hypercoherences → two

(extensionally) different notions of higher order

sequentiality. (Contrarily to what was expected, eg in [Lon02]).

(99)

Sequentiality

Non-uniform semantics : non-sequential, eg, {([t], t), ([f], t), ([t, f], t)}

is an agent of type !Bool Bool.

Multicoherence semantics: sequentiality at first order. Every finite agent of type

!(Bool & . . . & Bool) Bool is definable in PCF. Multicoherences 6= hypercoherences → two

(extensionally) different notions of higher order

sequentiality. (Contrarily to what was expected, eg in [Lon02]).

(100)

Sequentiality

Non-uniform semantics : non-sequential, eg, {([t], t), ([f], t), ([t, f], t)}

is an agent of type !Bool Bool.

Multicoherence semantics: sequentiality at first order. Every finite agent of type

!(Bool & . . . & Bool) Bool is definable in PCF. Multicoherences 6= hypercoherences → two

(extensionally) different notions of higher order

sequentiality. (Contrarily to what was expected, eg in [Lon02]).

(101)

References

[BE01] A. Bucciarelli and T. Ehrhard. On phase semantics and denotational semantics: the

exponentials. APAL, 109(3):205–241, 2001.

[Ehr96] Thomas Ehrhard. Projecting sequential

algorithms on strongly stable functions. APAL, 77, 1996.

[Lai01] J. Laird. Games and sequential algorithms.

Available by http, 2001.

[Lon02] J.R. Longley. The sequentially realizable functionals. APAL, 117(1-3):1–93, 2002.

[Mel01] Paul-André Melliès. Extensional collapse and coercions. Manuscript, December 2001.

(102)

References

[BE01] Antonio Bucciarelli and Thomas Ehrhard. On phase semantics and denotational semantics:

the exponentials. Annals of Pure and Applied Logic, 109(3):205–241, 2001.

[Ehr96] Thomas Ehrhard. Projecting sequential

algorithms on strongly stable functions. Annals of Pure and Applied Logic, 77, 1996.

[Lai01] J. Laird. Games and sequential algorithms.

Available by http, 2001.

[Lon02] J.R. Longley. The sequentially realizable

functionals. Annals of Pure and Applied Logic, 117(1-3):1–93, 2002.

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