TheoremBase

Second-Order Expansion of the N-Agent Cost about a Stationary Mean-Field Trajectory

Statement

Adopt the setting of the fluctuation processes of the controlled NN-agent dynamics: a transition-rate family β\beta on ll states with control set A\mathcal{A}, a nonempty subset of Euclidean space Rm\mathbb{R}^m, and rate bound BB, an observation-rate family β~\tilde{\beta}, a horizon T>0T>0, an NN-agent driving system, an observation-driven control policy hh which is A\mathcal{A}-valued, a solution on [0,T][0,T] with regular event Ω0\Omega_0, empirical state measure Σt\Sigma_t, and control αt\alpha_t, a mean-field trajectory pair (S,A)(S,A) for β\beta with horizon TT, and the fluctuation processes st=N(Σt−St)\mathfrak{s}_t=\sqrt{N}(\Sigma_t-S_t) and at=N(αt−At)\mathfrak{a}_t=\sqrt{N}(\alpha_t-A_t). Let (L,G)(L,G) be population cost data on ll states with control dimension mm, with NN-agent cost JN[h]J^N[h] and mean-field cost JMF[(S),(A)]J^{MF}[(S),(A)]. Let (U,V,βˉ)(U,V,\bar{\beta}) be a twice continuously differentiable extension of β\beta with derivative bound KK, let bˉ\bar{b} be the extended aggregate state drift of (U,V,βˉ)(U,V,\bar{\beta}), let (W,Lˉ,Gˉ)(W,\bar{L},\bar{G}) be a twice continuously differentiable extension of (L,G)(L,G) with second-derivative bound KcK_c, and let PP be a stationary co-state for these data, so that (S,A,P)(S,A,P) is a stationary mean-field triple. Adopt the partial-derivative notation ∂j∂i\partial_j\partial_i of the extension definitions, write dd for the Euclidean distance, ∣⋅∣|\cdot| for the Euclidean norm, E\mathbb{E} for the expectation, and Δl\Delta^l for the probability simplex, and let CPC_P be a real number with ∑δ=1l∣Ptδ∣≤CP\sum_{\delta=1}^{l}|P^\delta_t|\le C_P for all t∈[0,T]t\in[0,T], which exists because each component of PP is continuous on [0,T][0,T] by clause 1 of the co-state definition - relative to [0,T][0,T], with the metric of the real line - and therefore attains a maximum and a minimum on [0,T][0,T] by the extreme value theorem, hence is bounded.

Hypotheses. Assume that the control set A\mathcal{A} is convex and that A2=∫[0,T]E[∣at∣2] dt<∞\mathcal{A}_2=\int_{[0,T]}\mathbb{E}[|\mathfrak{a}_t|^2]\,dt<\infty, this integral being well defined by part (a) of the a priori second-moment bound; as in that lemma, the subscripted symbol A2\mathcal{A}_2 is distinct from the control set A\mathcal{A}.

For u≥0u\ge0 define

ωL(u)=sup⁡{∣∂j∂iLˉ(x)−∂j∂iLˉ(y)∣: i,j∈{1,…,l+m}, x,y∈Δl×Rm, d(x,y)≤u},\omega_L(u)=\sup\big\{|\partial_j\partial_i\bar{L}(x)-\partial_j\partial_i\bar{L}(y)|:\ i,j\in\{1,\dots,l+m\},\ x,y\in\Delta^l\times\mathbb{R}^m,\ d(x,y)\le u\big\}, ωb(u)=sup⁡{∣∂j∂ibˉγ(x)−∂j∂ibˉγ(y)∣: γ∈{1,…,l}, i,j∈{1,…,l+m}, x,y∈Δl×V, d(x,y)≤u},\omega_b(u)=\sup\big\{|\partial_j\partial_i\bar{b}^\gamma(x)-\partial_j\partial_i\bar{b}^\gamma(y)|:\ \gamma\in\{1,\dots,l\},\ i,j\in\{1,\dots,l+m\},\ x,y\in\Delta^l\times V,\ d(x,y)\le u\big\}, ωG(u)=sup⁡{∣∂δ∂γGˉ(Σ)−∂δ∂γGˉ(Σ′)∣: γ,δ∈{1,…,l}, Σ,Σ′∈Δl, d(Σ,Σ′)≤u}.\omega_G(u)=\sup\big\{|\partial_\delta\partial_\gamma\bar{G}(\Sigma)-\partial_\delta\partial_\gamma\bar{G}(\Sigma')|:\ \gamma,\delta\in\{1,\dots,l\},\ \Sigma,\Sigma'\in\Delta^l,\ d(\Sigma,\Sigma')\le u\big\}.

(a) (Moduli.) ωL\omega_L, ωb\omega_b, and ωG\omega_G are nondecreasing functions from [0,∞)[0,\infty) to [0,∞)[0,\infty) with ωL≤2Kc\omega_L\le2K_c, ωb≤6 l K\omega_b\le6\,l\,K, and ωG≤2Kc\omega_G\le2K_c everywhere, and for every ε>0\varepsilon>0 there is δ>0\delta>0 such that ωL(u)≤ε\omega_L(u)\le\varepsilon, ωb(u)≤ε\omega_b(u)\le\varepsilon, and ωG(u)≤ε\omega_G(u)\le\varepsilon for all u∈[0,δ]u\in[0,\delta].

(b) (Finiteness and eligibility.) JN[h]J^N[h] is finite; the pair ((s),(a))((\mathfrak{s}),(\mathfrak{a})) satisfies requirements (i)-(iii) of the fluctuation linear-quadratic cost (requirement (i) holding with Ω1=Ω0\Omega_1=\Omega_0 by the joint measurability of the state and control), so that LQG[(s),(a)]LQG[(\mathfrak{s}),(\mathfrak{a})] is a well-defined real number; and all expectations and integrals appearing in (c) are well defined and finite.

(c) (Expansion with quantitative remainder.) Set ζN=N (E[Σ0]−S0)∈Rl\zeta_N=N\,(\mathbb{E}[\Sigma_0]-S_0)\in\mathbb{R}^l, with the componentwise expectation, and set ρt=d((Σt,αt),(St,At))\rho_t=d\big((\Sigma_t,\alpha_t),(S_t,A_t)\big) for t∈[0,T]t\in[0,T], so that ρt=N−1/2(∣st∣2+∣at∣2)1/2\rho_t=N^{-1/2}\big(|\mathfrak{s}_t|^2+|\mathfrak{a}_t|^2\big)^{1/2} and d(ΣT,ST)=N−1/2∣sT∣d(\Sigma_T,S_T)=N^{-1/2}|\mathfrak{s}_T|. Then the real number RNR_N defined by the identity

N(JN[h]−JMF[(S),(A)])=LQG[(s),(a)]−∑γ=1lP0γ ζNγ+RNN\Big(J^N[h]-J^{MF}[(S),(A)]\Big)=LQG\big[(\mathfrak{s}),(\mathfrak{a})\big]-\sum_{\gamma=1}^{l}P^\gamma_0\,\zeta^\gamma_N+R_N

satisfies

∣RN∣ ≤ l+m2∫[0,T]E[(ωL(ρt)+CP ωb(ρt))(∣st∣2+∣at∣2)] dt + l2 E[ωG(d(ΣT,ST)) ∣sT∣2].|R_N|\ \le\ \frac{l+m}{2}\int_{[0,T]}\mathbb{E}\Big[\big(\omega_L(\rho_t)+C_P\,\omega_b(\rho_t)\big)\big(|\mathfrak{s}_t|^2+|\mathfrak{a}_t|^2\big)\Big]\,dt\ +\ \frac{l}{2}\,\mathbb{E}\Big[\omega_G\big(d(\Sigma_T,S_T)\big)\,|\mathfrak{s}_T|^2\Big].

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