Adopt the setting of the controlled N-agent dynamics: natural numbers N≥1, l≥2, l~≥1 and m≥1; a nonempty convex subset A of Euclidean space Rm, called the control set, which is compact for the topology determined by the Euclidean distance; a transition-rate family β on l states with control set A; an observation-rate family β~ on l states with l~ channels; a real number T>0; and an N-agent driving system (Ω,F,P) with initial states ς01,…,ς0N.
By Heine-Borel Theorem in Rn the set A is bounded, so there is a real number R≥0 with ∣a∣≤R for every a∈A, where ∣⋅∣ denotes the Euclidean norm. Let h=(hk)k≥0 be an observation-driven control policy with horizon T, control dimension m and l~ channels, with record spaces Rk(T), and assume h is A-valued.
Let (σi,Υυ,α) be a solution of the controlled N-agent dynamics on [0,T] for these data, with regular event Ω0, empirical state measure Σ, observation counters N~i,υ and observation total c~; such a solution exists by claim (ii) of the existence and uniqueness theorem. Thus Ω0 is an event of probability 1 at each of whose points the six conditions defining a solution hold, each counter N~ti,υ is a random variable that vanishes at every point outside Ω0, and c~t=∑i=1N∑υ=1l~N~ti,υ for t∈[0,T].
Adopt the notation of the Lebesgue space L2([0,T];Rd) in the case d=m, including the convention of claim 5 there by which an element of that space is denoted by the same symbol as a representative of it. Let UA be the set of A-valued controls and let ρ, dΔ, X and dX be as in the compactness lemma for the simplex, the control set and their product, the metric ρ being formed from a fixed sequence (wr)r∈N in L2([0,T];Rm) whose set of terms is dense there for the metric of that space, as in claim 1 of the weak metrizability and compactness theorem. Write B[0,T] and λ[0,T] for the restricted Borel σ-algebra and Lebesgue measure on [0,T], and let B[0,T]⊗F be the product σ-algebra. Fix a0∈A.
Then the following hold.
1. (A measurable observation record.) For each natural number j≥1 put
τj=inf{t∈[0,T]:c~t≥j},
the greatest lower bound of the displayed set when it is nonempty, with the convention τj=T+1 when it is empty. Then each τj is a random variable with values in [0,T]∪{T+1}, one has τ1(ω)≤τ2(ω)≤⋯ for every ω∈Ω, and
c~t(ω)≥jif and only ifτj(ω)≤t
for every ω∈Ω, every j≥1 and every t∈[0,T]. There are moreover random variables υj, indexed by the natural numbers j≥1, with values in {1,…,l~}, such that for every ω∈Ω0 and every j with 1≤j≤c~T(ω) the number τj(ω) is the j-th jump time of the observation total and υj(ω) is the channel attached to that jump time in condition 5 of the definition of a solution. Fix once and for all such a family (υj)j≥1; claims 2--5 below refer to it.
2. (The realized control.) Define α^:[0,T]×Ω→Rm by
α^(t,ω)=hk(t,τ1(ω),…,τk(ω),υ1(ω),…,υk(ω))with k=c~t(ω)
for ω∈Ω0, the right-hand side being h0(t) when k=0, and by α^(t,ω)=a0 for ω∈/Ω0. Then the argument of hk displayed above lies in [0,T]×Rk(T)×{1,…,l~}k, so that α^ is well defined; furthermore α^(t,ω)∈A for every t∈[0,T] and every ω∈Ω; one has α^(t,ω)=αt(ω) for every t∈[0,T] and every ω∈Ω0; and every component of α^ is measurable with respect to B[0,T]⊗F and the Borel σ-algebra of the real line.
3. (Each path is an A-valued control.) For every ω∈Ω the path t↦α^(t,ω) is square-integrable and every one of its values lies in A. Writing α^(ω) both for that path and for the element of L2([0,T];Rm) it represents, one has α^(ω)∈UA. Since every value of the path lies in A, the path is in particular a representative of α^(ω) that is A-valued at every point of [0,T], which is what claim 2 of the flow stability lemma calls an admissible representative.
4. (Weak distances are measurable.) For every ζ∈UA the map ω↦ρ(α^(ω),ζ) is a random variable.
5. (Random elements.) The map ω↦α^(ω) is a random element of (UA,ρ); the map Σ0 is a random element of (Δl,dΔ); and the map ω↦(Σ0(ω),α^(ω)) is a random element of (X,dX).