Weak Dynamic Programming for Viscosity Solutions · 2013-04-16 ·...
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Weak Dynamic Programming for ViscositySolutions
B. Bouchard
Ceremade, Univ. Paris-Dauphine, and, Crest, Ensae
May 2009
Joint work with Nizar Touzi, CMAP, Ecole Polytechnique
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Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X νt = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X νt = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
-
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X νt = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X νt = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
-
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X νt = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X νt = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
-
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X νt = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X νt = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
-
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X νt = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X νt = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
-
Motivations
• Consider the control problem in standard form
V (t, x) := supν∈U
J(t, x ; ν) , J(t, x ; ν) := E [f (X νT )|X νt = x ]
• To derive the related HJB equation, one uses the DPP
′′V (t, x) = supν∈U
E [V (τ,X ντ )|X νt = x ]′′
• Usually not that easy to prove
a Heavy measurable selection argument ?(t, x) 7→ νε(t, x) s.t. J(t, x ; νε(t, x)) ≥ V (t, x)− ε
b Continuity of the value function ?(t, x) ∈ Bri (ti , xi ) 7→ νε(ti , xi ) s.t.J(t, x ; νε(ti , xi )) ≥ J(ti , xi ; νε(ti , xi ))− ε ≥ V (ti , xi )− 2ε ≥ V (t, x)− 3ε
• Our aim is to provide a weak version, much easier to prove.
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Framework
• (Ω,F ,F := (Ft)t≤T ,P), T > 0.
• Controls :
U0, a collection of Rd -valued progressively measurable processes.
• Controlled process :
(τ, ξ; ν) ∈ S × U0 7−→ X ντ,ξ ∈ H0rcll(Rd )
with [0,T ]× Rd ⊂ S ⊂{
(τ, ξ) : τ ∈ T[0,T ] and ξ ∈ L0τ (Rd )}.
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Framework
• (Ω,F ,F := (Ft)t≤T ,P), T > 0.
• Controls :
U0, a collection of Rd -valued progressively measurable processes.
• Controlled process :
(τ, ξ; ν) ∈ S × U0 7−→ X ντ,ξ ∈ H0rcll(Rd )
with [0,T ]× Rd ⊂ S ⊂{
(τ, ξ) : τ ∈ T[0,T ] and ξ ∈ L0τ (Rd )}.
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Framework
• (Ω,F ,F := (Ft)t≤T ,P), T > 0.
• Controls :
U0, a collection of Rd -valued progressively measurable processes.
• Controlled process :
(τ, ξ; ν) ∈ S × U0 7−→ X ντ,ξ ∈ H0rcll(Rd )
with [0,T ]× Rd ⊂ S ⊂{
(τ, ξ) : τ ∈ T[0,T ] and ξ ∈ L0τ (Rd )}.
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Reward and Value functions
• Reward function
J(t, x ; ν) := E[f(X νt,x(T )
)]defined for controls ν in
U :={ν ∈ U0 : E
[|f (X νt,x(T ))|
]
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Reward and Value functions
• Reward function
J(t, x ; ν) := E[f(X νt,x(T )
)]defined for controls ν in
U :={ν ∈ U0 : E
[|f (X νt,x(T ))|
]
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Reward and Value functions
• Reward function
J(t, x ; ν) := E[f(X νt,x(T )
)]defined for controls ν in
U :={ν ∈ U0 : E
[|f (X νt,x(T ))|
]
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AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ ν̃ω ∈ Uθ(ω) s.t.
E[f(X νt,x(T )
)|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); ν̃ω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν̃ ∈ Us , and ν̄ := ν1[0,θ] + ν̃1(θ,T ] :
E[f(X ν̄t,x(T )
)|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν̃) for P− a.e. ω ∈ Ω.
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AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ ν̃ω ∈ Uθ(ω) s.t.
E[f(X νt,x(T )
)|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); ν̃ω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν̃ ∈ Us , and ν̄ := ν1[0,θ] + ν̃1(θ,T ] :
E[f(X ν̄t,x(T )
)|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν̃) for P− a.e. ω ∈ Ω.
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AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ ν̃ω ∈ Uθ(ω) s.t.
E[f(X νt,x(T )
)|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); ν̃ω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν̃ ∈ Us , and ν̄ := ν1[0,θ] + ν̃1(θ,T ] :
E[f(X ν̄t,x(T )
)|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν̃) for P− a.e. ω ∈ Ω.
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AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ ν̃ω ∈ Uθ(ω) s.t.
E[f(X νt,x(T )
)|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); ν̃ω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν̃ ∈ Us , and ν̄ := ν1[0,θ] + ν̃1(θ,T ] :
E[f(X ν̄t,x(T )
)|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν̃) for P− a.e. ω ∈ Ω.
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AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :a. For P-a.e ω ∈ Ω, ∃ ν̃ω ∈ Uθ(ω) s.t.
E[f(X νt,x(T )
)|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); ν̃ω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν̃ ∈ Us , and ν̄ := ν1[0,θ] + ν̃1(θ,T ] :
E[f(X ν̄t,x(T )
)|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν̃) for P− a.e. ω ∈ Ω.
-
AssumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :a. For P-a.e ω ∈ Ω, ∃ ν̃ω ∈ Uθ(ω) s.t.
E[f(X νt,x(T )
)|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); ν̃ω)
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν̃ ∈ Us , and ν̄ := ν1[0,θ] + ν̃1(θ,T ] :
E[f(X ν̄t,x(T )
)|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν̃) for P− a.e. ω ∈ Ω.
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The case where J(·; ν) is l.s.c. and V is continuous• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X νt,x(τ))
]′′
• Easy inequality : V (t, x) ≤ supν∈Ut E[V (τ,X νt,x(τ))
]
Proof :
V (t, x) = supν∈Ut
E[E[f (X νt,x(T ))|Fτ
]]where for some ν̃ω ∈ Uτ(ω)
E[f (X νt,x(T ))|Fτ
](ω) ≤ J(τ(ω),X νt,x(τ)(ω); ν̃ω)
≤ V (τ(ω),X νt,x(τ)(ω))
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The case where J(·; ν) is l.s.c. and V is continuous• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X νt,x(τ))
]′′• Easy inequality : V (t, x) ≤ supν∈Ut E
[V (τ,X νt,x(τ))
]
Proof :
V (t, x) = supν∈Ut
E[E[f (X νt,x(T ))|Fτ
]]where for some ν̃ω ∈ Uτ(ω)
E[f (X νt,x(T ))|Fτ
](ω) ≤ J(τ(ω),X νt,x(τ)(ω); ν̃ω)
≤ V (τ(ω),X νt,x(τ)(ω))
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The case where J(·; ν) is l.s.c. and V is continuous• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X νt,x(τ))
]′′• Easy inequality : V (t, x) ≤ supν∈Ut E
[V (τ,X νt,x(τ))
]Proof :
V (t, x) = supν∈Ut
E[E[f (X νt,x(T ))|Fτ
]]
where for some ν̃ω ∈ Uτ(ω)
E[f (X νt,x(T ))|Fτ
](ω) ≤ J(τ(ω),X νt,x(τ)(ω); ν̃ω)
≤ V (τ(ω),X νt,x(τ)(ω))
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The case where J(·; ν) is l.s.c. and V is continuous• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X νt,x(τ))
]′′• Easy inequality : V (t, x) ≤ supν∈Ut E
[V (τ,X νt,x(τ))
]Proof :
V (t, x) = supν∈Ut
E[E[f (X νt,x(T ))|Fτ
]]where for some ν̃ω ∈ Uτ(ω)
E[f (X νt,x(T ))|Fτ
](ω) ≤ J(τ(ω),X νt,x(τ)(ω); ν̃ω)
≤ V (τ(ω),X νt,x(τ)(ω))
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The case where J(·; ν) is l.s.c. and V is continuous• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X νt,x(τ))
]′′• Easy inequality : V (t, x) ≤ supν∈Ut E
[V (τ,X νt,x(τ))
]Proof :
V (t, x) = supν∈Ut
E[E[f (X νt,x(T ))|Fτ
]]where for some ν̃ω ∈ Uτ(ω)
E[f (X νt,x(T ))|Fτ
](ω) ≤ J(τ(ω),X νt,x(τ)(ω); ν̃ω)
≤ V (τ(ω),X νt,x(τ)(ω))
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The case where J(·; ν) is l.s.c. and V is continuous
• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X νt,x(τ))
]′′• Easy inequality :
V (t, x) ≤ supν∈Ut
E[V (τ,X νt,x(τ))
]
• More difficult one :
V (t, x) ≥ supν∈Ut
E[V (τ,X νt,x(τ))
]
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The case where J(·; ν) is l.s.c. and V is continuous
• Aim : Prove the DPP for τ ∈ T t[t,T ] (independent on Ft)
′′V (t, x) = supν∈Ut
E[V (τ,X νt,x(τ))
]′′• Easy inequality :
V (t, x) ≤ supν∈Ut
E[V (τ,X νt,x(τ))
]• More difficult one :
V (t, x) ≥ supν∈Ut
E[V (τ,X νt,x(τ))
]
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The case where J(·; ν) is l.s.c. and V is continuous
Proof : Using Vitali’s covering Lemma, find (ti , xi , ri , νi )i≥1 suchthat,
J(t, x ; ν i ) + ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )− ε ≥ V (t, x)− 2ε,
on (ti − ri , ti ]× Bri (xi ) and also on Ai := (ti − ri , ti ]× Bi , apartition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,τ ]ν + 1(τ,T ]∑i≥1
1Ai (τ,Xνt,x(τ))ν
i .
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The case where J(·; ν) is l.s.c. and V is continuous
Proof : Using Vitali’s covering Lemma, find (ti , xi , ri , νi )i≥1 suchthat,
J(t, x ; ν i ) + ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )− ε ≥ V (t, x)− 2ε,
on (ti − ri , ti ]× Bri (xi )
and also on Ai := (ti − ri , ti ]× Bi , apartition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,τ ]ν + 1(τ,T ]∑i≥1
1Ai (τ,Xνt,x(τ))ν
i .
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The case where J(·; ν) is l.s.c. and V is continuous
Proof : Using Vitali’s covering Lemma, find (ti , xi , ri , νi )i≥1 suchthat,
J(t, x ; ν i ) + ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )− ε ≥ V (t, x)− 2ε,
on (ti − ri , ti ]× Bri (xi ) and also on Ai := (ti − ri , ti ]× Bi , apartition of [t,T ]× Rd .
Given ν ∈ Ut , define
νε := 1[t,τ ]ν + 1(τ,T ]∑i≥1
1Ai (τ,Xνt,x(τ))ν
i .
-
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Using Vitali’s covering Lemma, find (ti , xi , ri , νi )i≥1 suchthat,
J(t, x ; ν i ) + ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )− ε ≥ V (t, x)− 2ε,
on (ti − ri , ti ]× Bri (xi ) and also on Ai := (ti − ri , ti ]× Bi , apartition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,τ ]ν + 1(τ,T ]∑i≥1
1Ai (τ,Xνt,x(τ))ν
i .
-
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X ν
ε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); νi )1Ai
(τ,X νt,x(τ)
)
≥∑i≥1
(V (τ,X νt,x(τ))− 3ε
)1Ai(τ,X νt,x(τ)
)= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X ν
ε
t,x(T ))|Fτ]]
≥ E[V(τ,X νt,x(τ)
)]− 3ε .
-
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X ν
ε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); νi )1Ai
(τ,X νt,x(τ)
)≥
∑i≥1
(V (τ,X νt,x(τ))− 3ε
)1Ai(τ,X νt,x(τ)
)
= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X ν
ε
t,x(T ))|Fτ]]
≥ E[V(τ,X νt,x(τ)
)]− 3ε .
-
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X ν
ε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); νi )1Ai
(τ,X νt,x(τ)
)≥
∑i≥1
(V (τ,X νt,x(τ))− 3ε
)1Ai(τ,X νt,x(τ)
)= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X ν
ε
t,x(T ))|Fτ]]
≥ E[V(τ,X νt,x(τ)
)]− 3ε .
-
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X ν
ε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); νi )1Ai
(τ,X νt,x(τ)
)≥
∑i≥1
(V (τ,X νt,x(τ))− 3ε
)1Ai(τ,X νt,x(τ)
)= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X ν
ε
t,x(T ))|Fτ]]
≥ E[V(τ,X νt,x(τ)
)]− 3ε .
-
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X ν
ε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); νi )1Ai
(τ,X νt,x(τ)
)≥
∑i≥1
(V (τ,X νt,x(τ))− 3ε
)1Ai(τ,X νt,x(τ)
)= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X ν
ε
t,x(T ))|Fτ]]
≥ E[V(τ,X νt,x(τ)
)]− 3ε .
-
The case where J(·; ν) is l.s.c. and V is continuous
Proof : Then,
E[f(X ν
ε
t,x(T ))|Fτ]
=∑i≥1
J(τ,X νt,x(τ); νi )1Ai
(τ,X νt,x(τ)
)≥
∑i≥1
(V (τ,X νt,x(τ))− 3ε
)1Ai(τ,X νt,x(τ)
)= V (τ,X νt,x(τ))− 3ε
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X ν
ε
t,x(T ))|Fτ]]
≥ E[V(τ,X νt,x(τ)
)]− 3ε .
-
Problems
• The lower-semicontinuity of J(·; ν) is very important in thisproof
: It is in general not difficult to obtain.
• The upper-semicontinuity of V is also very important
: It ismuch more difficult to obtain, especially when controls are notuniformly bounded (singular control).
-
Problems
• The lower-semicontinuity of J(·; ν) is very important in thisproof : It is in general not difficult to obtain.
• The upper-semicontinuity of V is also very important
: It ismuch more difficult to obtain, especially when controls are notuniformly bounded (singular control).
-
Problems
• The lower-semicontinuity of J(·; ν) is very important in thisproof : It is in general not difficult to obtain.
• The upper-semicontinuity of V is also very important
: It ismuch more difficult to obtain, especially when controls are notuniformly bounded (singular control).
-
Problems
• The lower-semicontinuity of J(·; ν) is very important in thisproof : It is in general not difficult to obtain.
• The upper-semicontinuity of V is also very important : It ismuch more difficult to obtain, especially when controls are notuniformly bounded (singular control).
-
Observation
To derive the PDE in the viscosity sense, try to obtain :
V (t, x) ≥ supν∈Ut
E[V (τ,X νt,x(τ)
]
but one only needs :
V (t, x) ≥ supν∈Ut
E[ϕ(τ,X νt,x(τ)
]for all smooth function such that (t, x) achieves a minimum ofV − ϕ.ϕ being smooth it should be much easier to prove ! !
-
Observation
To derive the PDE in the viscosity sense, try to obtain :
V (t, x) ≥ supν∈Ut
E[V (τ,X νt,x(τ)
]but one only needs :
V (t, x) ≥ supν∈Ut
E[ϕ(τ,X νt,x(τ)
]for all smooth function such that (t, x) achieves a minimum ofV − ϕ.
ϕ being smooth it should be much easier to prove ! !
-
Observation
To derive the PDE in the viscosity sense, try to obtain :
V (t, x) ≥ supν∈Ut
E[V (τ,X νt,x(τ)
]but one only needs :
V (t, x) ≥ supν∈Ut
E[ϕ(τ,X νt,x(τ)
]for all smooth function such that (t, x) achieves a minimum ofV − ϕ.ϕ being smooth it should be much easier to prove ! !
-
The weak DPPAssume that for all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut
lim inf(t′,x ′)→(t,x), t′≤t
J(t ′, x ′; ν) ≥ J(t, x ; ν).
Theorem : Fix {θν , ν ∈ Ut} ⊂ T t[t,T ] a family of stopping times.
Then, for any upper-semicontinuous function ϕ such that V ≥ ϕon [t,T ]× Rd , we have
V (t, x) ≥ supν∈Uϕt
E[ϕ(θν ,X νt,x(θ
ν))],
where Uϕt ={ν ∈ Ut : E
[ϕ(θν ,X νt,x(θ
ν))+]
-
The weak DPPAssume that for all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut
lim inf(t′,x ′)→(t,x), t′≤t
J(t ′, x ′; ν) ≥ J(t, x ; ν).
Theorem : Fix {θν , ν ∈ Ut} ⊂ T t[t,T ] a family of stopping times.Then, for any upper-semicontinuous function ϕ such that V ≥ ϕon [t,T ]× Rd , we have
V (t, x) ≥ supν∈Uϕt
E[ϕ(θν ,X νt,x(θ
ν))],
where Uϕt ={ν ∈ Ut : E
[ϕ(θν ,X νt,x(θ
ν))+]
-
The weak DPPAssume that for all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut
lim inf(t′,x ′)→(t,x), t′≤t
J(t ′, x ′; ν) ≥ J(t, x ; ν).
Theorem : Fix {θν , ν ∈ Ut} ⊂ T t[t,T ] a family of stopping times.Then, for any upper-semicontinuous function ϕ such that V ≥ ϕon [t,T ]× Rd , we have
V (t, x) ≥ supν∈Uϕt
E[ϕ(θν ,X νt,x(θ
ν))],
where Uϕt ={ν ∈ Ut : E
[ϕ(θν ,X νt,x(θ
ν))+]
-
The weak DPPAssume that for all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut
lim inf(t′,x ′)→(t,x), t′≤t
J(t ′, x ′; ν) ≥ J(t, x ; ν).
Theorem : Fix {θν , ν ∈ Ut} ⊂ T t[t,T ] a family of stopping times.Then, for any upper-semicontinuous function ϕ such that V ≥ ϕon [t,T ]× Rd , we have
V (t, x) ≥ supν∈Uϕt
E[ϕ(θν ,X νt,x(θ
ν))],
where Uϕt ={ν ∈ Ut : E
[ϕ(θν ,X νt,x(θ
ν))+]
-
The weak DPPProof.
For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]∑i≥1
1Ai (θν ,X νt,x(θ
ν))ν i .
Then,
E[f(X ν
ε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X νt,x(θ
ν))
≥∑i≥1
(ϕ(θν ,X νt,x(θ
ν))− 3ε)1Ai(θν ,X νt,x(θ
ν))
= ϕ(θν ,X νt,x(θν))− 3ε
-
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .
Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]∑i≥1
1Ai (θν ,X νt,x(θ
ν))ν i .
Then,
E[f(X ν
ε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X νt,x(θ
ν))
≥∑i≥1
(ϕ(θν ,X νt,x(θ
ν))− 3ε)1Ai(θν ,X νt,x(θ
ν))
= ϕ(θν ,X νt,x(θν))− 3ε
-
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]∑i≥1
1Ai (θν ,X νt,x(θ
ν))ν i .
Then,
E[f(X ν
ε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X νt,x(θ
ν))
≥∑i≥1
(ϕ(θν ,X νt,x(θ
ν))− 3ε)1Ai(θν ,X νt,x(θ
ν))
= ϕ(θν ,X νt,x(θν))− 3ε
-
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]∑i≥1
1Ai (θν ,X νt,x(θ
ν))ν i .
Then,
E[f(X ν
ε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X νt,x(θ
ν))
≥∑i≥1
(ϕ(θν ,X νt,x(θ
ν))− 3ε)1Ai(θν ,X νt,x(θ
ν))
= ϕ(θν ,X νt,x(θν))− 3ε
-
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]∑i≥1
1Ai (θν ,X νt,x(θ
ν))ν i .
Then,
E[f(X ν
ε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X νt,x(θ
ν))
≥∑i≥1
(ϕ(θν ,X νt,x(θ
ν))− 3ε)1Ai(θν ,X νt,x(θ
ν))
= ϕ(θν ,X νt,x(θν))− 3ε
-
The weak DPPProof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that
J(t, x ; ν i )+ε ≥ J(ti , xi ; ν i ) ≥ V (ti , xi )−ε ≥ ϕ(ti , xi )−ε ≥ ϕ(t, x)−2ε,
on Ai := (ti − ri , ti ]× Bi , a partition of [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]∑i≥1
1Ai (θν ,X νt,x(θ
ν))ν i .
Then,
E[f(X ν
ε
t,x(T ))|Fνθ]
=∑i≥1
J(θν ,X νt,x(θν); ν i )1Ai
(θν ,X νt,x(θ
ν))
≥∑i≥1
(ϕ(θν ,X νt,x(θ
ν))− 3ε)1Ai(θν ,X νt,x(θ
ν))
= ϕ(θν ,X νt,x(θν))− 3ε
-
The weak DPP
Proof. For i ≥ 1, fix ri > 0 and ν i ∈ Uti such that onAi := (ti − ri , ti ]× Bi , disjoint sets that cover [t,T ]× Rd .Given ν ∈ Ut , define
νε := 1[t,θν ]ν + 1(θν ,T ]∑i≥1
1Ai (θν ,X νt,x(θ
ν))ν i .
and
V (t, x) ≥ J(t, x ; νε)
= E[E[f(X ν
ε
t,x(T ))|Fνθ]]
≥ E[ϕ(θν ,X νt,x(θ
ν))]− 3ε .
-
The weak DPP
Using test functions makes the proof straightforward :
supν∈Uϕt
E[ϕ(θν ,X νt,x(θ
ν))]≤ V (t, x)
≤ supν∈Ut
E[V ∗(θν ,X νt,x(θ
ν))]
Remark : If {X νt,x(θν), ν ∈ Ut} is bounded in L∞, one canapproximate V∗ from below by smooth functions and obtain :
supν∈Ut
E[V∗(θν ,X νt,x(θ
ν))]≤ V (t, x) ≤ sup
ν∈UtE[V ∗(θν ,X νt,x(θ
ν))]
-
The weak DPP
Using test functions makes the proof straightforward :
supν∈Uϕt
E[ϕ(θν ,X νt,x(θ
ν))]≤ V (t, x) ≤ sup
ν∈UtE[V ∗(θν ,X νt,x(θ
ν))]
Remark : If {X νt,x(θν), ν ∈ Ut} is bounded in L∞, one canapproximate V∗ from below by smooth functions and obtain :
supν∈Ut
E[V∗(θν ,X νt,x(θ
ν))]≤ V (t, x) ≤ sup
ν∈UtE[V ∗(θν ,X νt,x(θ
ν))]
-
The weak DPP
Using test functions makes the proof straightforward :
supν∈Uϕt
E[ϕ(θν ,X νt,x(θ
ν))]≤ V (t, x) ≤ sup
ν∈UtE[V ∗(θν ,X νt,x(θ
ν))]
Remark : If {X νt,x(θν), ν ∈ Ut} is bounded in L∞, one canapproximate V∗ from below by smooth functions and obtain :
supν∈Ut
E[V∗(θν ,X νt,x(θ
ν))]≤ V (t, x) ≤ sup
ν∈UtE[V ∗(θν ,X νt,x(θ
ν))]
-
Example : Framework
• Controlled process
dX (r) = µ (X (r), νr ) dr + σ (X (r), νr ) dWr
• U = square integrable progressively measurable processes withvalues in U ⊂ Rd
• f is l.s.c with f − with linear growth, µ and σ Lipschitzcontinuous.
-
Example : Framework
• Controlled process
dX (r) = µ (X (r), νr ) dr + σ (X (r), νr ) dWr
• U = square integrable progressively measurable processes withvalues in U ⊂ Rd
• f is l.s.c with f − with linear growth, µ and σ Lipschitzcontinuous.
-
Example : Framework
• Controlled process
dX (r) = µ (X (r), νr ) dr + σ (X (r), νr ) dWr
• U = square integrable progressively measurable processes withvalues in U ⊂ Rd
• f is l.s.c with f − with linear growth, µ and σ Lipschitzcontinuous.
-
Example : Verification of the assumptions
For all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
L.s.c. (t ′, x ′)→ (t, x) ⇒ X νt′,x ′(T )→ X νt,x(T ) in L2
⇒ lim inf E[f (X νt′,x ′(T ))
]≥ E
[f (X νt,x(T ))
].
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
-
Example : Verification of the assumptions
For all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
L.s.c. (t ′, x ′)→ (t, x) ⇒ X νt′,x ′(T )→ X νt,x(T ) in L2
⇒ lim inf E[f (X νt′,x ′(T ))
]≥ E
[f (X νt,x(T ))
].
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
-
Example : Verification of the assumptions
For all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
L.s.c. (t ′, x ′)→ (t, x) ⇒ X νt′,x ′(T )→ X νt,x(T ) in L2
⇒ lim inf E[f (X νt′,x ′(T ))
]≥ E
[f (X νt,x(T ))
].
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
-
Example : Verification of the assumptions
For all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :
L.s.c. (t ′, x ′)→ (t, x) ⇒ X νt′,x ′(T )→ X νt,x(T ) in L2
⇒ lim inf E[f (X νt′,x ′(T ))
]≥ E
[f (X νt,x(T ))
].
A1 (Independence) The process X νt,x is independent of Ft .
A2 (Causality) ∀ ν̃ ∈ Ut : ν = ν̃ on A ⊂ F ⇒ X νt,x = X ν̃t,x on A.
A3 (Stability under concatenation) ∀ ν̃ ∈ Ut , θ ∈ T t[t,T ] :ν1[0,θ] + ν̃1(θ,T ] ∈ Ut .
-
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ ν̃ω ∈ Uθ(ω) s.t.
E[f(X νt,x(T )
)|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); ν̃ω)
Proof. Canonical space : W (ω) = ω. Set Ts(ω) := (ωr − ωs)r≥s andωs := (ωr∧s)r≥0.
Eˆf`X νt,x(T )
´|Fθ˜(ω) =
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))θ(ω),Xνt,x (θ)(ω)
(T )(Tθ(ω)(ω))«
dP(Tθ(ω)(ω)) .
=
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω̃))θ(ω),Xνt,x (θ)(ω)
(T )(Tθ(ω)(ω̃))«
dP(ω̃)
= J(θ(ω),X νt,x(θ)(ω); ν̃ω)
where, ν̃ω(ω̃) := ν(ωθ(ω) + Tθ(ω)(ω̃)) ∈ Uθ(ω).
-
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ ν̃ω ∈ Uθ(ω) s.t.
E[f(X νt,x(T )
)|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); ν̃ω)
Proof. Canonical space : W (ω) = ω. Set Ts(ω) := (ωr − ωs)r≥s andωs := (ωr∧s)r≥0.
Eˆf`X νt,x(T )
´|Fθ˜(ω) =
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))θ(ω),Xνt,x (θ)(ω)
(T )(Tθ(ω)(ω))«
dP(Tθ(ω)(ω)) .
=
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω̃))θ(ω),Xνt,x (θ)(ω)
(T )(Tθ(ω)(ω̃))«
dP(ω̃)
= J(θ(ω),X νt,x(θ)(ω); ν̃ω)
where, ν̃ω(ω̃) := ν(ωθ(ω) + Tθ(ω)(ω̃)) ∈ Uθ(ω).
-
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
a. For P-a.e ω ∈ Ω, ∃ ν̃ω ∈ Uθ(ω) s.t.
E[f(X νt,x(T )
)|Fθ]
(ω) ≤ J(θ(ω),X νt,x(θ)(ω); ν̃ω)
Proof. Canonical space : W (ω) = ω. Set Ts(ω) := (ωr − ωs)r≥s andωs := (ωr∧s)r≥0.
Eˆf`X νt,x(T )
´|Fθ˜(ω) =
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω))θ(ω),Xνt,x (θ)(ω)
(T )(Tθ(ω)(ω))«
dP(Tθ(ω)(ω)) .
=
Zf„
Xν(ωθ(ω)+Tθ(ω)(ω̃))θ(ω),Xνt,x (θ)(ω)
(T )(Tθ(ω)(ω̃))«
dP(ω̃)
= J(θ(ω),X νt,x(θ)(ω); ν̃ω)
where, ν̃ω(ω̃) := ν(ωθ(ω) + Tθ(ω)(ω̃)) ∈ Uθ(ω).
-
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν̃ ∈ Us , and ν̄ := ν1[0,θ] + ν̃1(θ,T ] :
E[f(X ν̄t,x(T )
)|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν̃) for P− a.e. ω ∈ Ω.
Proof.
Eˆf`X ν̄t,x(T )
´|Fθ˜(ω) =
Zf„
Xν̃(ωθ(ω)+Tθ(ω)(ω̃))θ(ω),Xνt,x (θ)(ω)
(T )(Tθ(ω)(ω̃))«
dP(ω̃),
and therefore
Eˆf`X ν̄t,x(T )
´|Fθ˜(ω) =
Zf“X ν̃(Ts (ω̃))θ(ω),Xνt,x (θ)(ω)(T )(Tθ(ω)(ω̃))
”dP(ω̃)
= J(θ(ω),X νt,x(θ)(ω); ν̃) .
-
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν̃ ∈ Us , and ν̄ := ν1[0,θ] + ν̃1(θ,T ] :
E[f(X ν̄t,x(T )
)|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν̃) for P− a.e. ω ∈ Ω.
Proof.
Eˆf`X ν̄t,x(T )
´|Fθ˜(ω) =
Zf„
Xν̃(ωθ(ω)+Tθ(ω)(ω̃))θ(ω),Xνt,x (θ)(ω)
(T )(Tθ(ω)(ω̃))«
dP(ω̃),
and therefore
Eˆf`X ν̄t,x(T )
´|Fθ˜(ω) =
Zf“X ν̃(Ts (ω̃))θ(ω),Xνt,x (θ)(ω)(T )(Tθ(ω)(ω̃))
”dP(ω̃)
= J(θ(ω),X νt,x(θ)(ω); ν̃) .
-
Example : Verification of the assumptionsFor all (t, x) ∈ [0,T ]× Rd and ν ∈ Ut :A4 (Consistency with deterministic initial data) ∀ θ ∈ T t[t,T ] :
b. ∀ t ≤ s ≤ T , θ ∈ T t[t,s], ν̃ ∈ Us , and ν̄ := ν1[0,θ] + ν̃1(θ,T ] :
E[f(X ν̄t,x(T )
)|Fθ]
(ω) = J(θ(ω),X νt,x(θ)(ω); ν̃) for P− a.e. ω ∈ Ω.
Proof.
Eˆf`X ν̄t,x(T )
´|Fθ˜(ω) =
Zf„
Xν̃(ωθ(ω)+Tθ(ω)(ω̃))θ(ω),Xνt,x (θ)(ω)
(T )(Tθ(ω)(ω̃))«
dP(ω̃),
and therefore
Eˆf`X ν̄t,x(T )
´|Fθ˜(ω) =
Zf“X ν̃(Ts (ω̃))θ(ω),Xνt,x (θ)(ω)(T )(Tθ(ω)(ω̃))
”dP(ω̃)
= J(θ(ω),X νt,x(θ)(ω); ν̃) .
-
Example : Super-solution property
• Want to prove that V∗ is a viscosity super-solution of
infu∈U
(−LuV∗) ≥ 0
• By usingV (t, x) ≥ sup
ν∈UϕtE[ϕ(θν ,X νt,x(θ
ν))]
-
Example : Super-solution property
• Want to prove that V∗ is a viscosity super-solution of
infu∈U
(−LuV∗) ≥ 0
• By usingV (t, x) ≥ sup
ν∈UϕtE[ϕ(θν ,X νt,x(θ
ν))]
-
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ̃(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ̃(t, x) ≤ 0 on Br := {|t − t0| ≤ r , |x − x0| ≤ r}.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := inf{s ≥ tn : (s,X utn,xn(s)) /∈ Br
}so that
V (tn, xn) + ιn = ϕ̃(tn, xn) ≤ E[ϕ̃(θn,X utn,xn(θn))
]
≤ E[ϕ(θn,X utn,xn(θn))
]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X utn,xn(θn))
]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X utn,xn(θn))
]by the weak DPP.
-
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ̃(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ̃(t, x) ≤ 0 on Br := {|t − t0| ≤ r , |x − x0| ≤ r}.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := inf{s ≥ tn : (s,X utn,xn(s)) /∈ Br
}so that
V (tn, xn) + ιn = ϕ̃(tn, xn) ≤ E[ϕ̃(θn,X utn,xn(θn))
]
≤ E[ϕ(θn,X utn,xn(θn))
]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X utn,xn(θn))
]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X utn,xn(θn))
]by the weak DPP.
-
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ̃(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ̃(t, x) ≤ 0 on Br := {|t − t0| ≤ r , |x − x0| ≤ r}.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := inf{s ≥ tn : (s,X utn,xn(s)) /∈ Br
}so that
V (tn, xn) + ιn = ϕ̃(tn, xn) ≤ E[ϕ̃(θn,X utn,xn(θn))
]
≤ E[ϕ(θn,X utn,xn(θn))
]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X utn,xn(θn))
]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X utn,xn(θn))
]by the weak DPP.
-
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ̃(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ̃(t, x) ≤ 0 on Br := {|t − t0| ≤ r , |x − x0| ≤ r}.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := inf{s ≥ tn : (s,X utn,xn(s)) /∈ Br
}so that
V (tn, xn) + ιn = ϕ̃(tn, xn) ≤ E[ϕ̃(θn,X utn,xn(θn))
]
≤ E[ϕ(θn,X utn,xn(θn))
]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X utn,xn(θn))
]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X utn,xn(θn))
]by the weak DPP.
-
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ̃(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ̃(t, x) ≤ 0 on Br := {|t − t0| ≤ r , |x − x0| ≤ r}.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := inf{s ≥ tn : (s,X utn,xn(s)) /∈ Br
}so that
V (tn, xn) + ιn = ϕ̃(tn, xn) ≤ E[ϕ̃(θn,X utn,xn(θn))
]
≤ E[ϕ(θn,X utn,xn(θn))
]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X utn,xn(θn))
]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X utn,xn(θn))
]by the weak DPP.
-
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ̃(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ̃(t, x) ≤ 0 on Br := {|t − t0| ≤ r , |x − x0| ≤ r}.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := inf{s ≥ tn : (s,X utn,xn(s)) /∈ Br
}so that
V (tn, xn) + ιn = ϕ̃(tn, xn) ≤ E[ϕ̃(θn,X utn,xn(θn))
]
≤ E[ϕ(θn,X utn,xn(θn))
]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X utn,xn(θn))
]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X utn,xn(θn))
]by the weak DPP.
-
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ̃(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ̃(t, x) ≤ 0 on Br := {|t − t0| ≤ r , |x − x0| ≤ r}.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := inf{s ≥ tn : (s,X utn,xn(s)) /∈ Br
}so that
V (tn, xn) + ιn = ϕ̃(tn, xn) ≤ E[ϕ̃(θn,X utn,xn(θn))
]≤ E
[ϕ(θn,X utn,xn(θn))
]− r4
for some ιn → 0
, i.e. V (tn, xn) ≤ E[ϕ(θn,X utn,xn(θn))
]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X utn,xn(θn))
]by the weak DPP.
-
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ̃(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ̃(t, x) ≤ 0 on Br := {|t − t0| ≤ r , |x − x0| ≤ r}.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := inf{s ≥ tn : (s,X utn,xn(s)) /∈ Br
}so that
V (tn, xn) + ιn = ϕ̃(tn, xn) ≤ E[ϕ̃(θn,X utn,xn(θn))
]≤ E
[ϕ(θn,X utn,xn(θn))
]− r4
for some ιn → 0, i.e. V (tn, xn) ≤ E[ϕ(θn,X utn,xn(θn))
]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X utn,xn(θn))
]by the weak DPP.
-
Example : Super-solution property
• (t0, x0) ∈ [0,T )× Rd s.t. 0 = (V∗ − ϕ)(t0, x0) = min(V∗ − ϕ)
• Assume that −Luϕ(t0, x0) < 0, for some u ∈ U.
• Set ϕ̃(t, x) := ϕ(t, x)− |t − t0|4 − |x − x0|4.
• Then, −Luϕ̃(t, x) ≤ 0 on Br := {|t − t0| ≤ r , |x − x0| ≤ r}.
• Fix (tn, xn,V (tn, xn))→ (t0, x0,V∗(t0, x0)).
• Set θn := inf{s ≥ tn : (s,X utn,xn(s)) /∈ Br
}so that
V (tn, xn) + ιn = ϕ̃(tn, xn) ≤ E[ϕ̃(θn,X utn,xn(θn))
]≤ E
[ϕ(θn,X utn,xn(θn))
]− r4
for some ιn → 0, i.e. V (tn, xn) ≤ E[ϕ(θn,X utn,xn(θn))
]− r4/2.
• While V (tn, xn) ≥ E[ϕ(θn,X utn,xn(θn))
]by the weak DPP.
-
Extensions
• Optimal control with running gain
• Optimal stopping
• Mixed optimal control/stopping, impulse control, ...
-
Extensions
• Optimal control with running gain
• Optimal stopping
• Mixed optimal control/stopping, impulse control, ...
-
Extensions
• Optimal control with running gain
• Optimal stopping
• Mixed optimal control/stopping, impulse control, ...