TheoremBase

Pointwise-in-Time Tracking of the Mean-Field Flow and Cost along the Realized Control of the Controlled N-Agent Dynamics

Statement

Adopt the setting, hypotheses, and notation of the comparison lemma for the NN-agent system and the mean-field flow: the affine-controlled transition-rate family (β0,β1)(\beta_0,\beta_1) on ll states with control set A⊆Rm\mathcal{A}\subseteq\mathbb{R}^m and its transition-rate family β\beta with rate bound BB, aggregate state drift bb, and state-Lipschitz constant Λb\Lambda_b; the observation-rate family β~\tilde{\beta}; the horizon T>0T>0; the population cost data (L,G)(L,G), convex in the control on A\mathcal{A}; the probability simplex Δl\Delta^l; the set UA\mathcal{U}_{\mathcal{A}} of A\mathcal{A}-valued controls with the metric ρ\rho of the compactness lemma for the simplex, the control set and their product, formed from the fixed dense sequence of claim 1 of the weak metrizability theorem — the same sequence, hence the same metric ρ\rho, being used in the boundedness, lower-semicontinuity and attainment theorem and in the realized-control lemma cited below; the mean-field flow S(x0,ξ)S(x_0,\xi) of claim 2 of the flow stability lemma; the mean-field cost F(x0,ξ)F(x_0,\xi); the NN-agent driving system (Ω,F,P)(\Omega,\mathcal{F},P), the A\mathcal{A}-valued observation-driven control policy hh, and the solution (σi,Υυ,α)(\sigma^i,\Upsilon^\upsilon,\alpha) with regular event Ω0\Omega_0 and empirical state measure Σ\Sigma; the realized control α^\hat{\alpha} of the realized-control lemma; the martingale part M=(M1,…,Ml)M=(M^1,\dots,M^l) of the martingale decomposition of the empirical state measure; the event Ω∗⊆Ω0\Omega_*\subseteq\Omega_0 of the martingale bound; and the random variable WW of claim 2 of the comparison lemma, so that W(ω)=∫[0,T]L(Σt(ω),α^(t,ω)) dt+G(ΣT(ω))W(\omega)=\int_{[0,T]}L(\Sigma_t(\omega),\hat{\alpha}(t,\omega))\,dt+G(\Sigma_T(\omega)) for ω∈Ω∗\omega\in\Omega_* and JN[h]=E[W]J^N[h]=\mathbb{E}[W]. Write ∣⋅∣|\cdot| for the Euclidean norm, E\mathbb{E} for the expectation, exp⁡\exp for the exponential function, and ∫[0,t]⋅ ds\int_{[0,t]}\cdot\,ds for the Lebesgue integral over the compact interval [0,t][0,t], taken to be 00 for t=0t=0. For every ω∈Ω\omega\in\Omega write Sω=S(Σ0(ω),α^(ω))S^\omega=S(\Sigma_0(\omega),\hat{\alpha}(\omega)) for the mean-field flow started at the realized initial state and driven by the realized control; it is defined for every ω\omega by claim 2 of the flow stability lemma, since Σ0(ω)∈Δl\Sigma_0(\omega)\in\Delta^l and α^(ω)∈UA\hat{\alpha}(\omega)\in\mathcal{U}_{\mathcal{A}}, and on Ω∗\Omega_* it is the SωS^\omega of claim 1 of the comparison lemma. Write b^\hat{b} for the projected drift of claim 6 of the affine-rate lemma. Set

KM=2+2(l−1)BT,Γ=1+ΛbTexp⁡(ΛbT).K_M=2+2(l-1)BT,\qquad \Gamma=1+\Lambda_bT\exp(\Lambda_bT).

(LipC) (Lipschitz cost data.) Assume there are real numbers KL≥0K_L\ge0 and KG≥0K_G\ge0 such that ∣L(Σ,a)−L(Σ′,a)∣≤KL∣Σ−Σ′∣|L(\Sigma,a)-L(\Sigma',a)|\le K_L|\Sigma-\Sigma'| and ∣G(Σ)−G(Σ′)∣≤KG∣Σ−Σ′∣|G(\Sigma)-G(\Sigma')|\le K_G|\Sigma-\Sigma'| for all Σ,Σ′∈Δl\Sigma,\Sigma'\in\Delta^l and all a∈Aa\in\mathcal{A}. This hypothesis is used in claim 3 and in the estimate of claim 4 only. (The constant KMK_M defined above is that of the martingale bound.)

Then the following hold.

1. (Paths of the martingale part.) For every ω∈Ω0\omega\in\Omega_0 and every γ∈{1,…,l}\gamma\in\{1,\dots,l\} the path t↦Mtγ(ω)t\mapsto M^\gamma_t(\omega) is measurable with respect to the trace Borel σ\sigma-algebra on [0,T][0,T] and the Borel σ\sigma-algebra on the real line, and ∣Mtγ(ω)∣≤KM|M^\gamma_t(\omega)|\le K_M for every t∈[0,T]t\in[0,T]; consequently t↦∣Mt(ω)∣t\mapsto|M_t(\omega)| is measurable and bounded by l KM\sqrt{l}\,K_M (with ⋅\sqrt{\cdot} the nonnegative square root), and the integrals Mt(ω)=∫[0,t]∣Ms(ω)∣ ds\mathcal{M}_t(\omega)=\int_{[0,t]}|M_s(\omega)|\,ds exist for every t∈[0,T]t\in[0,T] and are nondecreasing in tt.

2. (Pointwise-in-time tracking of the flow.) For every ω∈Ω0\omega\in\Omega_0 and every t∈[0,T]t\in[0,T],

∣Σt(ω)−Stω∣ ≤ ∣Mt(ω)∣+Λbexp⁡(Λbt) Mt(ω).\big|\Sigma_t(\omega)-S^\omega_t\big|\ \le\ |M_t(\omega)|+\Lambda_b\exp(\Lambda_bt)\,\mathcal{M}_t(\omega).

3. (Tracking of the cost.) Under (LipC), for every ω∈Ω∗\omega\in\Omega_*,

∣W(ω)−F(Σ0(ω),α^(ω))∣ ≤ KL Γ MT(ω)+KG(∣MT(ω)∣+Λbexp⁡(ΛbT) MT(ω)).\big|W(\omega)-F\big(\Sigma_0(\omega),\hat{\alpha}(\omega)\big)\big|\ \le\ K_L\,\Gamma\,\mathcal{M}_T(\omega)+K_G\Big(|M_T(\omega)|+\Lambda_b\exp(\Lambda_bT)\,\mathcal{M}_T(\omega)\Big).

4. (Shift of the initial state.) Let z0∈Δlz_0\in\Delta^l. The map ω↦F(z0,α^(ω))\omega\mapsto F\big(z_0,\hat{\alpha}(\omega)\big) is a random variable, and under (LipC), for every ω∈Ω\omega\in\Omega,

∣F(Σ0(ω),α^(ω))−F(z0,α^(ω))∣ ≤ (KLT+KG)exp⁡(ΛbT) ∣Σ0(ω)−z0∣.\big|F\big(\Sigma_0(\omega),\hat{\alpha}(\omega)\big)-F\big(z_0,\hat{\alpha}(\omega)\big)\big|\ \le\ (K_LT+K_G)\exp(\Lambda_bT)\,\big|\Sigma_0(\omega)-z_0\big| .

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