Reason: Proof of the strengthened adaptedness lemma: outright observation-filtration measurability of the control is now derived, the generic square-integrability transfer is replaced by a citation to the new lemma, and the final step is renumbered.
Proof
Fix t∈[0,T] and j∈{1,…,m}. Throughout, Gt is the σ-algebra generated by the random variables Υsυ (0≤s≤t, υ∈{1,…,l~}) together with every event of probability 0, as in the solution definition.
Step 0 (preliminaries). We use repeatedly: finite sums, differences, products, and scalar multiples of Gt-measurable real-valued functions on Ω are Gt-measurable, and indicator functions of events of Gt are Gt-measurable --- the rational-decomposition argument recorded in the stochastic-process definition and the level-set arguments of the Preliminaries of the square-integrability definition use only the generator criterion of the definition of a measurable function, and therefore apply verbatim with Gt in place of F. Likewise, for countably many Gt-measurable functions X1,X2,…, the pointwise infimum infnXn, when real-valued, is Gt-measurable, since {infnXn<a}=⋃n{Xn<a} for every real a, and similarly supnXn via {supnXn>a}=⋃n{Xn>a}; in particular the maximum and minimum of two Gt-measurable real-valued functions are Gt-measurable, being the supremum and infimum of a two-element family. From the sets {X<a} (respectively {X>a}) for all real a one recovers the preimages of all Borel sets by complements and countable set operations, by the generator criterion.
Step 1 (observation totals). For s∈[0,t] set Ks′=N∑υ=1l~Υsυ, a Gt-measurable random variable. At every ω∈Ω0 and every s∈[0,t], condition 4 of the solution definition gives Υsυ=N1∑i=1NN~si,υ, so Ks′=∑i,υN~si,υ=c~s, the observation total. For k=0,1,2,… put Gk={Kt′=k}∈Gt; these events are pairwise disjoint, and we write G∞=Ω∖⋃k≥0Gk.
Step 2 (counting-path facts and jump-time surrogates). Let c be a counting path, let k≥1 be a natural number with c(t′)≥k for some t′≥0, and let τk(c) be its k-th jump time. We record:
(i) for every q≥0: c(q)≥k if and only if q≥τk(c). Indeed, for every s>τk(c) the greatest-lower-bound property yields s′∈[τk(c),s) with c(s′)≥k, so c(s)≥k by monotonicity (clause 2 of the counting-path definition); then c(τk(c))≥k by right-continuity (clause 3: c(τk(c)) is the greatest lower bound of {c(s):s>τk(c)}, a set with all members ≥k), and c(q)≥k for q≥τk(c) by monotonicity. Conversely c(q)≥k puts q in the set whose infimum is τk(c).
(ii)τk(c)>0: otherwise c(0)≥k≥1 by (i), contradicting c(0)=0 (clause 1).
(iii)c(τk(c))=k, and τk(c) is a jump time of c: every s<τk(c) has c(s)≤k−1 by (i) and integrality (clause 1), so c(τk(c)−)≤k−1, while c(τk(c))≥k by (i); the unit-jump bound (clause 4) gives k≤c(τk(c))≤c(τk(c)−)+1≤k, so c(τk(c))=k>c(τk(c)−).
(iv) if also c(t′′)≥k+1 for some t′′, then τk(c)<τk+1(c): by (iii), c(τk(c))=k<k+1, so τk(c)≥τk+1(c) would contradict (i) applied to k+1.
(v) for T′>0, the jump times of c lying in (0,T′] are exactly τ1(c)<⋯<τc(T′)(c): each τk(c) with k≤c(T′) lies in (0,T′] by (i)--(ii) and is a jump time by (iii). Conversely let t′′∈(0,T′] be a jump time and put k=c(t′′). The set {c(s):0≤s<t′′} is a nonempty set of integers bounded above, so its least upper bound c(t′′−) is a member of the set (there is a member exceeding c(t′′−)−1; a strictly larger member would be an integer in an interval of length less than 1 above it, so that member is the least upper bound); in particular c(t′′−) is an integer, and clause 4 with c(t′′−)<c(t′′) gives c(t′′−)=k−1 and k≥1. Every s<t′′ then has c(s)≤k−1<k while c(t′′)=k, so τk(c)=t′′ by the definition of the infimum. Hence the jump times in (0,T′] all occur among τ1(c),…,τc(T′)(c), which are strictly increasing by (iv), and the two finite lists coincide.
By condition 3 of the solution definition, s↦c~s coincides on [0,T] with the restriction of a counting path c, and condition 5 lists the jump times of the observation total in [0,T] as τ1<⋯<τKT; by fact (v) with T′=T these are exactly τ1(c)<⋯<τc(T)(c) (jump times are positive by definition, so lying in [0,T] means lying in (0,T], and c(T)=c~T=KT, so the two lists have the same length), and facts (i)--(iv) apply to them, with c(q)=c~q for q∈[0,T].
Now let D=(Q∩[0,t])∪{t}, a countable set containing t. For j′≥1 define
τj′′(ω)=inf({q∈D:Kq′(ω)≥j′}∪{t}),
a well-defined element of [0,t]. For a≤t, {τj′′<a}=⋃q∈D,q<a{Kq′≥j′} (an infimum of a set is smaller than a exactly when some member is), and for a>t, {τj′′<a}=Ω; in all cases an event of Gt, so τj′′ is Gt-measurable. Set τj′′′=max(τ1′,…,τj′′), again Gt-measurable, with 0≤τ1′′≤τ2′′≤⋯≤t at every ω, so that for every k≥1 the tuple (τ1′′,…,τk′′) lies in the record space Rk(T) of the policy definition.
Claim: at every ω∈Ω0 with c~t(ω)≥j′, τj′′(ω)=τj′(ω). Indeed, by Step 1 and fact (i), for q∈D one has Kq′=c~q≥j′ exactly when q≥τj′, so the set in the infimum is D∩[τj′,t], which contains t. If τj′<t, its infimum is τj′: no member is smaller, and for every q′>τj′ there are rational numbers in (τj′,min(q′,t)) by the density of the rationals in the real numbers; if τj′=t, the set is {t} with infimum t. Since the jump times increase in j′ (fact (iv)), also τj′′′(ω)=τj′(ω) for all j′≤c~t(ω) at every ω∈Ω0.
Step 3 (channel surrogates). Fix j′≥1; the construction below is carried out for every j′, and we suppress the index j′ on dn, en, Unυ, Lnυ, Vυ, Wυ, retaining it on the resulting υj′′. For n∈N let Qn={it2−n:i=0,1,…,2n}⊆[0,t], a finite set containing 0 and t. Define dn=min{q∈Qn:q≥τj′′} and en=max({q∈Qn:q<τj′′}∪{0}); both are Gt-measurable with finitely many values: each event {dn=q} and {en=q} is a countable Boolean combination of events {τj′′<a} with a real, all in Gt by Step 2, using {τj′′≤q′}=⋂n′≥1{τj′′<q′+1/n′}. For υ∈{1,…,l~} set
Gt-measurable random variables; since the events {dn=q}, q∈Qn, partition Ω, and likewise the events {en=q}, one has Unυ=Υdnυ and Lnυ=Υenυ pointwise. Set
Each truncated term lies between 0 and max(Υtυ,0) at every ω, so Vυ and Wυ are real-valued everywhere and Gt-measurable by Step 0.
At every ω∈Ω0: by condition 3 of the solution definition, each s↦N~si,υ coincides on [0,T] with the restriction of a counting path, so s↦Υsυ=N1∑iN~si,υ is nondecreasing and nonnegative on [0,T]. For finitely many nondecreasing paths, at every time the greatest lower bound over strictly later times of the sum is the sum of the greatest lower bounds, and the least upper bound over strictly earlier times of the sum is the sum of the least upper bounds: given ε′′>0, a single later (respectively earlier) time can be chosen that works for all summands at once, by monotonicity. Hence right-continuity (clause 3 of the counting-path definition) passes to Υυ at every s∈[0,T) --- and since the paths are nondecreasing, the greatest lower bound over all s′>s is already attained over s′∈(s,T], so Υsυ=inf{Υs′υ:s<s′≤T} --- the left limit Υs−υ=sup{Υs′υ:0≤s′<s} exists for s∈(0,T], and
Υsυ−Υs−υ=N1i=1∑N(N~si,υ−N~s−i,υ),
which is positive exactly when some observation counter with channel υ jumps at s, every summand being nonnegative. Moreover 0≤Unυ≤Υtυ and 0≤Lnυ≤Υtυ on Ω0 (monotonicity, since dn,en∈[0,t]), so the truncations are inactive there: Vυ=infnΥdnυ and Wυ=supnΥenυ at every ω∈Ω0.
If moreover c~t(ω)≥j′: then τj′′=τj′ (Step 2), and dn≥τj′ with dn−τj′≤t2−n, so every term satisfies Υdnυ≥Υτj′υ by monotonicity, and infnΥdnυ=Υτj′υ: either dn=τj′ for some n, or dn>τj′ for all n, in which case dn≤t forces τj′<t≤T, right-continuity applies at τj′∈[0,T), and for every s>τj′ one has dn≤s for all large n, so the infimum equals the displayed greatest lower bound Υτj′υ. And τj′>0 by fact (ii) of Step 2, so for n with t2−n<τj′ one has en<τj′ and τj′−en≤t2−n, whence supnΥenυ=sup{Υsυ:0≤s<τj′}=Υτj′−υ by monotonicity.
Define υj′′ as the least υ∈{1,…,l~} with Vυ>Wυ, and υj′′=1 if there is no such υ; each event {υj′′=υ} is a finite Boolean combination of the events {Vυ′′>Wυ′′}∈Gt. At every ω∈Ω0 with c~t(ω)≥j′: by condition 5 of the solution definition exactly one observation counter jumps at τj′, and its channel is υj′; by the displayed jump identity, Υτj′υ−Υτj′−υ>0 exactly when υ=υj′; hence Vυ>Wυ exactly for υ=υj′, and υj′′=υj′.
Step 4 (assembly). Fix k≥1 and a mark vector v∈{1,…,l~}k, and write {υ′=v} for the event {υ1′=v1}∩⋯∩{υk′=vk}. The policy definition makes (t′,τ)↦hkj(t′,τ,v) measurable for the σ-algebra generated by the relatively open subsets of [0,T]×Rk(T). The insertion map ι:Rk(T)→[0,T]×Rk(T), ι(τ)=(t,τ) with the present t fixed, pulls relatively open sets back to relatively open sets: if U is an open subset of R1+k and τ∈Rk(T) with (t,τ)∈U, there is an open box around (t,τ) inside U, whose slice at first coordinate t is an open box around τ whose intersection with Rk(T) is contained in the preimage; so the preimage of U∩([0,T]×Rk(T)) is relatively open in Rk(T). Since the collection of subsets of [0,T]×Rk(T) whose ι-preimage lies in the σ-algebra generated by the relatively open subsets of Rk(T) is a σ-algebra containing the relatively open sets, the slice gk,v∘:τ↦hkj(t,τ,v), which is hkj(⋅,⋅,v)∘ι, is measurable for the σ-algebra generated by the relatively open subsets of Rk(T). Next, the map ω↦τ′′(ω)=(τ1′′(ω),…,τk′′(ω))∈Rk(T) pulls relatively open sets back to Gt: every open subset of Rk is the union of the countably many open boxes with rational vertices that it contains (around every point of an open set there is such a box, by the definition of openness via balls and the density of the rationals), and the preimage of an open box is a finite intersection of events {a<τj′′′<b}∈Gt, while the preimage of U∩Rk(T) equals the preimage of U because the map takes values in Rk(T). Since the collection of subsets of Rk(T) whose preimage under ω↦τ′′(ω) lies in Gt is a σ-algebra containing the relatively open sets, the composite gk,v:ω↦gk,v∘(τ′′(ω))=hkj(t,(τ1′′(ω),…,τk′′(ω)),v) is Gt-measurable.
where at each ω at most one summand is nonzero (the events Gk are pairwise disjoint and, for fixed k, the mark events {υ′=v} over v partition Ω), and the value is 0 on G∞. This is a well-defined real-valued function, and it is Gt-measurable: for every Borel set A,
a countable union of events of Gt (the conditions h0j(t)∈A and 0∈A select ∅ or the displayed event).
Step 5 (identity on the regular event). Let ω∈Ω0 and put k=c~t(ω)=Kt′(ω) (Step 1), so ω∈Gk. If k=0, condition 5 of the solution definition gives αtj(ω)=h0j(t)=αt′j(ω). If k≥1, then for 1≤j′≤k Steps 2--3 give τj′′′(ω)=τj′(ω) and υj′′(ω)=υj′(ω), so with v=(υ1(ω),…,υk(ω)) the active summand is gk,v(ω)=hkj(t,(τ1(ω),…,τk(ω)),v)=αtj(ω) by condition 5. This gives the random variable αt′j of conclusion 1, the almost-sure equality following from P(Ω0)=1.
Finally, αtj is itself Gt-measurable. The control process is one of the families of random variables constituting a solution, so αtj is F-measurable, and for every Borel setA′′ of the real line
Now Ω∖Ω0 is an event of F of probability 0, so it lies in Gt, and therefore so does Ω0; the first set on the right is thus an intersection of two members of Gt. The second set is an event of F contained in Ω∖Ω0, hence of probability 0 by claim 2 of the basic properties of a measure, and hence again a member of Gt. So {αtj∈A′′}∈Gt, which completes conclusion 1.
Step 6 (fluctuation control). With (S,A) and at as in conclusion 2, Atj is a real number. Hence atj=N(αtj−Atj) is Gt-measurable, by the Gt-measurability of αtj established in Step 5 together with the closure of Gt-measurability under scalar multiples and addition of constants (Step 0). For the same reason N(αt′j−Atj) is Gt-measurable, and at every ω∈Ω0 it equals N(αtj(ω)−Atj)=atj(ω) by conclusion 1 and the definition of the control fluctuation process; since P(Ω0)=1, the two are almost surely equal. The last assertion of conclusion 2 is then the transfer lemma for almost sure equality, applied with X=atj and Y=N(αt′j−Atj). □