Abstract
An existence result for a class of mean field games of controls is provided. In the considered model, the cost functional to be minimized by each agent involves a price depending at a given time on the controls of all agents and a congestion term. The existence of a classical solution is demonstrated with the Leray–Schauder theorem; the proof relies in particular on a priori bounds for the solution, which are obtained with the help of a potential formulation of the problem.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
1 Introduction
The goal of this work is to prove the existence and uniqueness of a classical solution to the following system of partial differential equations:
where \(u=u(x,t) \in \mathbb {R}\), \(m=m(x,t) \in \mathbb {R}\), \(v=v(x,t) \in \mathbb {R}^d\), \(P= P(t) \in \mathbb {R}^k\), with \((x,t) \in Q:=\mathbb {T}^d\times [0,T]\). The parameters \(T>0\), \(\sigma >0\) are given and
are given data. The set \(\mathcal {D}_1(\mathbb {T}^d)\) is defined as
We work with \(\mathbb {Z}^d\)-periodic data and we set the state set as the d-dimensional torus \(\mathbb {T}^d\), that is a quotient set \(\mathbb {R}^d / \mathbb {Z}^d\). The Hamiltonian H is assumed to be such that \(H(x,t,p)= L^*(x,t,-p)\), for some mapping L, where \(L^*(x,t,p)\) denotes the Fenchel transform with respect to p:
The mapping L is assumed to be convex in its third variable.
The function u, as a solution to the Hamilton–Jacobi–Bellman (HJB) in equation (i) (MFGC) is the value function corresponding to the stochastic optimal control problem:
subject to the stochastic dynamics \(\mathrm {d} X_s = \alpha _s \, \mathrm {d} s + \sqrt{2\sigma } \, \mathrm {d} B_s , \; X_t = x \in \mathbb {T}^d\). The feedback law v given by (iv) (MFGC) is then optimal for this stochastic optimal control problem. Equation (ii) (MFGC) is the Fokker–Planck equation which describes the evolution of the distribution m(t) of the agents, when the optimal feedback law is employed. At last, (iii) (MFGC) makes the quantity \(P(t)\) endogenous.
An interpretation of the system (MFGC) is as follows. Consider a stock trading market. A typical trader, with an initial level of stock \(X_0=x\), controls its level of stock \((X_t)_{ t \in [0,T]}\) through the purchasing rate \(\alpha _t\) with stochastic dynamic \(\mathrm {d} X_t = \alpha _t \mathrm {d} t+ \sqrt{2 \sigma } \mathrm {d} B_t\). The agent aims at minimizing the expected cost (2) where \(P(t)\) is the price of the stock at time t. The agent is considered to be infinitesimal and has no impact on \(P(t)\), so it assumes the price as given in its optimization problem. On the other hand, in the equilibrium configuration, the price \(P(t) \; (t \in [0,T])\) becomes endogenous and indeed, is a function of the optimal behaviour of the whole population of agents as formulated in (iii) (MFGC). The expression \(D(t) := \int _{ \mathbb {T}^d} \phi (x,t) v(x,t) m(x,t) \; \mathrm {d} x\) can be considered as a weighted net demand formulation and the relation \(P = \varPsi (D)\) is the result of supply-demand relation which determines the price of the good at the market. Concerning the role of the mapping \(\phi \), one can think for example to the case of two exchangeable goods, i.e. \(x \in \mathbb {R}^2\), with a price given by \(P(t)= \varPsi ( \int _{\mathbb {T}^d} (\phi _1(x,t)v_1(x,t)+\phi _2(x,t) v_2(x,t)) m(x,t) \, \text {d} x )\), where \(\varPsi :\mathbb {R}\rightarrow \mathbb {R}\). The use of a mapping \(\phi \), which is valued in \(\mathbb {R}^{1 \times 2}\) and whose values depend on the scale choosed for the goods, is in such a situation necessary. Thus, the system (MFGC) captures an equilibrium configuration. Similar models have been proposed in the electrical engineering literature, see for example [2, 10, 11] and the references therein.
In most mean field game models, the individual players interact through their position only, that is, via the variable m. The problem that we consider belongs to the more general class of problems, called extended mean field games, for which the players interact through the joint probability distribution \(\mu \) of states and controls. Several existence results have been obtained for such models: in [13] for stationary mean field games, in [15] for deterministic mean field games. In [6, Section 5], a class of problems where \(\mu \) enters in the drift and the integral cost of the agents is considered. We adopt the terminology mean field games of controls employed by the authors of the latter reference. Let us mention that our existence proof is different from the one of [6], which includes control bounds. In [3, Section 1], a model where the drift of the players depends on \(\mu \) is analyzed. In [14], a mean field game model is considered where at all time t, the average control (with respect to all players) is prescribed. We finally mention that extended mean field games have been studied with a probabilistic approach in [1, 8] and in [7, Section 4.6], and that a class of linear-quadratic extended mean field games has been analyzed in [20].
A difficulty in the study of mean field games of controls, directly related to the supply-demand relation mentioned above, is the fact that the control variable, at a given time t, cannot be expressed in an explicit fashion as a function of \(m(\cdot ,t)\) and \(u(\cdot ,t)\). Instead, one has to analyze the well-posedness and the stability of a fixed point equation (see for example [6, Lemma 5.2]). In our model, if we combine (iii) and (iv) (MFGC), we obtain the fixed point equation
for the control variable v. A central idea of the present article is the following: equation (3) is equivalent to the optimality conditions of a convex optimization problem, when L is convex and \(\varPsi \) is the gradient of a convex function \(\varPhi \). This observation allows to show the existence and uniqueness of a solution v (to equation (3)) and to investigate its dependence with respect to \(\nabla u\) and m in a natural way. More precisely, we prove that this dependence is locally Hölder continuous.
The existence of a classical solution of (MFGC) is established with the Leray–Schauder theorem and classical estimates for parabolic equations. A similar approach has been employed in [16, 17], and [18] for the analysis of a mean field game problem proposed by Chan and Sircar [9]. In this model, each agent exploits an exhaustible resource and fixes its price. The evolution of the capacity of a given producer depends on the price set by the producer, but also on the average price (with respect to all producers).
The application of the Leray–Schauder theorem relies on a priori bounds for fixed points. These bounds are obtained in particular with a potential formulation of the mean field game problem: we prove that all solutions to (MFGC) are also solutions to an optimal control problem of the Fokker–Planck equation. We are not aware of any other publication making use of such a potential formulation for a mean field game of controls, with the exception of [17] for the Chan and Sircar model. Let us mention that besides the derivation of a priori bounds, the potential formulation of the problem can be very helpful for the numerical resolution of the problem and the analysis of learning procedures (which are out of the scope of the present work).
The article is structured as follows. We list in Sect. 2 the assumptions employed all along. The main result (Theorem 1) is stated in Sect. 3. We provide in Sect. 4 a first incomplete potential formulation of the problem, incomplete in so far as the term f(m) is not integrated. We also introduce some auxiliary mappings, which allow to express P and v as functions of m and u. We give some regularity properties for these mappings in Sect. 5. In Sect. 6 we establish some a priori bounds for solutions to the coupled system. We prove our main result in Sect. 7. In Sec. 8, we give a full potential formulation of the problem, prove the uniqueness of the solution to (MFGC) and prove that (u, P, f(m)) is the solution to an optimal control problem of the HJB equation, under an additional monotonicity condition on f. Some parabolic estimates, used all along the article, are provided and proved in the appendix.
2 Assumptions on Data
Let us introduce the main notation used in the article. Recall that \(\mathcal {D}_1(\mathbb {T}^d)\) was defined in (1). For all \(m \in \mathcal {D}_1(\mathbb {T}^d)\), for all measurable functions \(v :\mathbb {T}^d\rightarrow \mathbb {R}^d\) such that \(|v(\cdot )|^2 m(\cdot )\) is integrable, the following inequality holds true,
by the Cauchy–Schwarz inequality.
The gradient of the data functions with respect to some variable is denoted with an index, for example, \(H_p\) denotes the gradient of H with respect to p. The same notation is used for the Hessian matrix. The gradient of u with respect to x is denoted by \(\nabla u\). Let us mention that very often, the variables x and t are omitted, to alleviate the calculations. We also denote by \(\int \phi v m\) the integral \(\int _{\mathbb {T}^d} \phi v m \; \mathrm {d} x\) when used as a second argument of \(\varPsi \). For a given normed space X, the ball of center 0 and radius R is denoted B(X, R).
Along the article, we use the following Hölder spaces: \(\mathcal {C}^\alpha (Q)\), \(\mathcal {C}^{2+ \alpha }(\mathbb {T}^d)\), and \(\mathcal {C}^{2+ \alpha ,1+\alpha /2}(Q)\), defined as usual with \(\alpha \in (0,1)\). Sobolev spaces are denoted by \(W^{k,p}\), the order of derivation k being possibly non-integral (see their definition in [19, section II.2]). We fix now a real number p such that
We will also make use of the following Banach space:
2.1 Convexity Assumptions
We collect below the required assumptions on the data. As announced in the introduction, H is related to the convex conjugate of a mapping \(L :Q \times \mathbb {R}^d \rightarrow \mathbb {R}\) as follows:
The mapping L is assumed to be strongly convex in its third variable, uniformly in x and t, that is, we assume that L is differentiable with respect to v and that there exists \(C> 0\) such that
for all \((x,t) \in Q\) and for all \(v_1\) and \(v_2 \in \mathbb {R}^d\). This ensures that H takes finite values and that H is continuously differentiable with respect to p, as can be easily checked. Moreover, the supremum in (5) is reached for a unique v, which is then given by \(v= -H_p(x,t,p)\), i.e.
for all \((x,t,p,v) \in Q \times \mathbb {R}^d \times \mathbb {R}^d\).
We also assume that \(\varPsi \) has a potential, that is, there exists a mapping \(\varPhi :[0,T] \times \mathbb {R}^k \rightarrow \mathbb {R}\), differentiable in its second argument, such that
2.2 Regularity Assumptions
We assume that \(L_v\) is differentiable with respect to x and v and that \(\phi \) is differentiable with respect to x. All along the article, we make use of the following assumptions.
2.3 Growth Assumptions
There exists \(C>0\) such that for all \((x,t) \in Q\), \(y \in \mathbb {T}^d\), \(v \in \mathbb {R}^d\), \(z \in \mathbb {R}^k\), and \(m \in \mathcal {D}_1(\mathbb {T}^d)\),
2.4 Hölder Continuity Assumptions
-
For all \(R>0\), there exists \(\alpha \in (0,1)\) such that
$$\begin{aligned} {\left\{ \begin{array}{ll} \begin{array}{l} L \in \mathcal {C}^{\alpha }(B_R), \\ L_v \in \mathcal {C}^{\alpha }(B_R, \mathbb {R}^d), \\ L_{vx} \in \mathcal {C}^{\alpha }(B_R, \mathbb {R}^{d \times d}), \\ L_{vv} \in \mathcal {C}^{\alpha }(B_R, \mathbb {R}^{d \times d}), \end{array} \end{array}\right. } \quad {\left\{ \begin{array}{ll} \begin{array}{l} \varPsi \in \mathcal {C}^{\alpha }(B_R',\mathbb {R}^d), \\ \phi \in \mathcal {C}^{\alpha }(Q,\mathbb {R}^{k \times d}), \\ D_x \phi \in \mathcal {C}^{\alpha }(Q,\mathbb {R}^{k \times d \times d}), \end{array} \end{array}\right. } \qquad \end{aligned}$$(A6)where \(B_R= Q \times B(\mathbb {R}^d,R)\) and \(B_R'= [0,T] \times B(\mathbb {R}^k,R)\).
-
There exists \(\alpha \in (0,1)\) and \(C>0\) such that
$$\begin{aligned} \begin{aligned}&\qquad \qquad | f(x_2,t_2,m_2) - f(x_1,t_1,m_1) | \\&\qquad \qquad \qquad \le C \big ( |x_2 - x_1| + |t_2 - t_1|^\alpha + \Vert m_2 - m_1 \Vert _{L^{\infty }(\mathbb {T}^d)}^\alpha \big ), \end{aligned} \end{aligned}$$(A7)for all \((x_1,t_1)\) and \((x_2,t_2) \in Q\) and for all \(m_1\) and \(m_2 \in \mathcal {D}_1(\mathbb {T}^d)\).
-
$$\begin{aligned} \text {There exists }\alpha \in (0,1)\text { such that }m_0 \in \mathcal {C}^{2+ \alpha }(\mathbb {T}^d)\text {, }g \in \mathcal {C}^{2 +\alpha }(\mathbb {T}^d). \end{aligned}$$(A8)
Let us mention here that the variables \(C>0\) and \(\alpha \in (0,1)\) used all along the article are generic constants. The value of C may increase from an inequality to the next one and the value of the exponent \(\alpha \) may decrease.
Some lower bounds for L and for \(\varPhi \) can be easily deduced from the convexity assumptions. By assumption (A6), L(x, t, 0) and \(L_v(x,t,0)\) are bounded. It follows then from the strong convexity assumption (A1) that there exists a constant \(C> 0\) such that
Without loss of generality, we can assume that \(\varPhi (t,0)=0\), for all \(t \in [0,T]\). Since \(\varPhi \) is convex, we have that \(\varPhi (t,z) \ge \langle \varPsi (t,0), z \rangle \), for all \(z \in \mathbb {R}^k\). We deduce then from assumption (A4) that
where C is independent of t and z.
Some regularity properties for the Hamiltonian can be deduced from the convexity assumption (A1) and the Hölder continuity of L and its derivatives (assumption (A6)). They are collected in the following lemma.
Lemma 1
The Hamiltonian H is differentiable with respect to p and \(H_p\) is differentiable with respect to x and p. Moreover, for all \(R>0\), there exists \(\alpha \in (0,1)\) such that \(H \in \mathcal {C}^{\alpha }(B_R)\), \(H_p \in \mathcal {C}^{\alpha }(B_R, \mathbb {R}^d)\), \(H_{px} \in \mathcal {C}^{\alpha }(B_R, \mathbb {R}^{d \times d})\), and \(H_{pp} \in \mathcal {C}^{\alpha }(B_R, \mathbb {R}^{d \times d})\)
Proof
For a given \((x,t,p) \in Q \times \mathbb {R}^d\), there exists a unique \(v:= v(x,t,p)\) maximizing the function \(v \in \mathbb {R}^d \mapsto -\langle p,v \rangle - {L(x,t,v)}\), which is strongly concave by (A1). It is then easy to deduce from (8) and the boundedness of L(x, t, 0) that there exists a constant C, independent of (x, t, p), such that \(|v(x,t,p)| \le C( |p| +1)\). For all \((x,t,p) \in Q \times \mathbb {R}^d\), we have
Since \(L_v\) is continuously differentiable with respect to x and v, we obtain with the inverse mapping theorem that v(x, t, p) is continuously differentiable with respect to x and p. Let \(R > 0\) and let \((x_1,t_1,p_1)\) and \((x_2,t_2,p_2) \in Q \times B_R\). Let \(v_i= v(x_i,t_i,p_i)\) for \(i=1,2\). We have \(|v_i| \le C\), where C does not depend on \(x_i\), \(t_i\), and \(p_i\) (but depends on R). Moreover, we have
We deduce from (A1), Young’s inequality, and (A6) that there exists \(C>0\) and \(\alpha \in (0,1)\), both independent of \(x_i\), \(t_i\), and \(p_i\) such that
for all \(\varepsilon > 0\). Taking \(\varepsilon = {1}/{2C}\), we deduce that the mapping \((x,t,p) \in B_R \mapsto v(x,t,p)\) is Hölder continuous. Since L is Hölder continuous on bounded sets, we obtain that the Hamiltonian \(H(x,t,p)= -\langle p,v(x,t,p) \rangle - L(x,t,v(x,t,p))\) is Hölder continuous on \(B_R\).
One can easily check that \(H_p(x,t,p)= -v(x,t,p)\), which proves that \(H_p\) is Hölder continuous on \(B_R\). Finally, differentiating relation (10) with respect to x and p, we obtain that
We deduce then with assumption (A6) that \(D_x v(x,t,p)\) and \(D_p v(x,t,p)\) (and thus \(H_{px}\) and \(H_{pp}\)) are Hölder continuous on \(B_R\), as was to be proved. \(\square \)
An example of coupling term We finish this section with an example of a mapping f satisfying the regularity assumptions (A5) and (A7). Let \(\varphi \in L^\infty (\mathbb {R}^d)\) be a given Lipschitz continuous mapping, with modulus \(C_1\). Let us set \(C_2= \Vert \varphi \Vert _{L^\infty (\mathbb {R}^d)}\). Let \(K :Q \times [-C_2,C_2] \rightarrow \mathbb {R}\) be a measurable mapping satisfying the following assumptions:
-
1.
The mapping \(x \in \mathbb {T}^d\mapsto K(x,0,0)\) lies in \(L^1(\mathbb {T}^d)\).
-
2.
There exist a mapping \(C_3 \in L^1(\mathbb {T}^d)\) and \(\alpha \in (0,1)\) such that for a.e. \(x \in \mathbb {T}^d\), for all \(t_1\) and \(t_2 \in [0,T]\) and for all \(w_1\) and \(w_2 \in [-C_2,C_2]\),
$$\begin{aligned} |K(x,t_2,w_2)-K(x,t_1,w_1)| \le C_3(x) \big ( |t_2-t_1|^\alpha + |w_2 - w_1|^\alpha \big ). \end{aligned}$$
Let us set \(\tilde{\varphi }(x) := \varphi (-x)\). We identify \(m\in L^\infty (\mathbb {T}^d)\) with its extension by 0 over \(\mathbb {R}^d\) so that the convolution product below is well-defined:
We keep in mind that \(m*\varphi \) is a function over \(\mathbb {T}^d\). Then
In a similar way we can define
and we have that
The specific structure of \(f_K\) is actually motivated by the fact that under an additional monotonicity assumption, \(f_K\) derives from a potential (as proved in [4, Example 1.1]). For the moment, we have the following regularity result.
Lemma 2
The above mapping \(f_K\) satisfies assumptions (A5) and (A7).
Proof
Assumption (A5) follows from (14). We next prove (A7). Let \((x_1,t_1)\) and \((x_2,t_2) \in Q\), let \(m_1\) and \(m_2 \in \mathcal {D}_1(\mathbb {T}^d)\). Then
Also,
Finally, we have \(\Vert (m_2 - m_1) * \varphi \Vert _{L^\infty (\mathbb {T}^d)} \le \Vert m_2 - m_1 \Vert _{L^\infty (\mathbb {T}^d)} \Vert \varphi \Vert _{L^\infty (\mathbb {T}^d)}\) and thus, assumption (A7) follows. \(\square \)
3 Main Result and General Approach
Theorem 1
There exists \(\alpha \in (0,1)\) such that (MFGC) has a classical solution (u, m, v, P), with
The result is obtained with the Leray–Schauder theorem, recalled below.
Theorem 2
(Leray–Schauder) Let X be a Banach space and let \(\mathcal {T} :X \times [0,1] \rightarrow X\) be a continuous and compact mapping. Let \(x_0 \in X\). Assume that \(\mathcal {T}(x,0)=x_0\) for all \(x \in X\) and assume there exists \(C>0\) such that \(\Vert x \Vert _X < C\) for all \((x,\tau ) \in X \times [0,1]\) such that \(\mathcal {T} (x,\tau ) = x\). Then, there exists \(x \in X\) such that \(\mathcal {T}(x,1) = x\).
A proof of the theorem can be found in [12, Theorem 11.6], for \(x_0=0\). The extension to a general value of \(x_0\) can be easily obtained with a translation argument that we do not detail. The application of the Leray–Schauder theorem and the construction of \(\mathcal {T}\) will be detailed in Sect. 7. Let us mention that the set of fixed points of \(\mathcal {T}(\cdot ,\tau )\), for \(\tau \in [0,1]\), will coincide with the set of solutions of the following parametrization of (MFGC):
Of course, (MFGC\(_\tau \)) corresponds to (MFGC) for \(\tau = 1\). Let us introduce the spaces X and \(X'\), used for the formulation of the fixed-point equation:
The HJB equation (i) and the Fokker–Planck equation (ii) are classically understood in the viscosity and weak sense, respectively. However, due to the choice of the solution spaces, we may interpret these equations as equalities in \(L^p(Q)\): in particular, if \(u \in W^{2,1,p}(Q)\) and \(P \in L^\infty (0,T;\mathbb {R}^k)\), we have that \(\nabla u \in L^\infty (Q;\mathbb {R}^d)\) (by Lemma 12), and thus \(H(\nabla u + \phi ^\intercal P(t)) \in L^\infty (Q)\). A first and important step of our analysis is the construction of auxiliary mappings allowing to express v and P as functions of m and u. These mappings cannot be obtained in a straightforward way, since in (iii), P depends on v and in (iv), v depends on P.
Lemma 3
Let \(\tau \in [0,1]\), let \((m,v) \in W^{2,1,p}(Q) \times L^\infty (Q,\mathbb {R}^d)\) be a weak solution to the Fokker–Planck equation \(\partial _t m - \sigma \varDelta m + \tau \text {div }(vm)= 0\), \(m(\cdot ,0)= m_0(\cdot )\). Then \(m \ge 0\) and for all \(t \in [0,T]\), \(\int _{\mathbb {T}^d} m(x,t) \; \mathrm {d} x = 1\).
Proof
Multiply (MFGC\(_\tau \))(ii) by \(\mu (x,t):=\min (0,m(x,t))\). Use \(\nabla \mu (x,t)=\mathbf{1}_{\{m(x,t)<0\}} \nabla m(x,t)\), so that integrating (by parts) over \(Q_t:=\mathbb {T}^d\times (0,t)\), since v is essentially bounded, we get that
so that after cancellation of the contribution of \(\nabla \mu \), we obtain, applying Gronwall’s lemma to \(a(t):=\int _{\mathbb {T}^d} \mu (x,t)^2\), that \(a(t)=0\) for all t which means that m is non-negative. Moreover, for all \(t \in [0,T]\),
Integrating by parts the double integral we see that it is equal to 0, and we conclude by noting that \(\int _{\mathbb {T}^d} m(x,0) \; \mathrm {d} x = \int _{\mathbb {T}^d} m_0(x) \; \mathrm {d} x = 1\). \(\square \)
4 Potential Formulation
In this section, we first establish a potential formulation of the mean field game problem (MFGC\(_\tau \)), that is to say, we prove that for \((u_\tau ,m_\tau ,v_\tau ,P_\tau ) \in X'\) satisfying (MFGC\(_\tau \)), \((m_\tau ,v_\tau )\) is a solution to an optimal control problem. We prove then that for all t, \(v_\tau (\cdot ,t)\) is the unique solution of some optimization problem, which will enable us to construct the announced auxiliary mappings.
Let us introduce the cost functional \(B :W^{2,1,p}(Q) \times L^\infty (Q,\mathbb {R}^d) \times L^\infty (Q) \rightarrow \mathbb {R}\), defined by
We have the following result.
Lemma 4
For all \(\tau \in [0,1]\) and \((u_\tau ,m_\tau ,v_\tau ,P_\tau ) \in X'\) satisfying (MFGC\(_\tau \)), the pair \((m_\tau ,v_\tau )\) is the solution to the following optimization problem:
where \(\tilde{f}_\tau (x,t)= f(x,t,m_\tau (t))\).
Remark 1
Let us emphasize that the above optimal control problem is only an incomplete potential formulation, since the term \(\tilde{f}_\tau \) still depends on \(m_\tau \).
Proof
(Lemma 4) Let us consider the case where \(\tau \in (0,1]\). Let \((m,v) \in W^{2,1,p}(Q) \times L^\infty (Q,\mathbb {R}^d)\) be a feasible pair, i.e., it satisfies the constraint in (17). For all \((x,t) \in Q\), we have \(v_\tau = - H_p(\nabla u_\tau + \phi ^\intercal P_\tau )\). Therefore, by (5) and (6), we have that
for all \((x,t) \in Q\). Moreover, by Lemma 3, \(m \ge 0\) and \(m_\tau \ge 0\). Therefore,
Using (i) (MFGC\(_\tau \)), we obtain
After integration with respect to x, we obtain that for all t,
We obtain with the convexity of \(\varPhi \) and (iii) (MFGC\(_\tau \)) that
Using the previous calculations to bound \(B(m,v;\tilde{f}_\tau )-B(m_\tau ,v_\tau ;\tilde{f}_\tau )\) from below, we observe that the term \(\langle P_\tau , {\textstyle \int }\phi (m - m_\tau v_\tau ) \rangle \) cancels out and obtain
Integrating by parts and using (ii) (MFGC\(_\tau \)), we finally obtain that
as was to be proved. We do not detail the proof for the case \(\tau =0\), which is actually simpler. Indeed, for \(\tau =0\), the solution to the Fokker–Planck equation is independent of v and thus \(m= m_\tau \) in the above calculations. \(\square \)
We have proved that the pair \((m_\tau ,v_\tau )\) is the solution to an optimal control problem. Therefore, for all t, \(v_\tau (\cdot ,t)\) minimizes the Hamiltonian associated with problem (17). Let us introduce some notation, in order to exploit this property. For \(m \in \mathcal {D}_1(\mathbb {T}^d)\), we denote by \(L_m^2(\mathbb {T}^d,\mathbb {R}^d)\) the Hilbert space of measurable mappings \(v :\mathbb {T}^d\rightarrow \mathbb {R}^d\) such that \(\int _{\mathbb {T}^d} |v|^2 m < \infty \), equipped with the scalar product \(\int _{\mathbb {T}^d} \langle v_1,v_2 \rangle m\). An element of \(L_m^2(\mathbb {T}^d)\) is an equivalent class of functions equal m-almost everywhere. Note that \(L^\infty (\mathbb {T}^d) \subset L_m^2(\mathbb {T}^d)\).
For \(t \in [0,T]\), \(m \in \mathcal {D}_1(\mathbb {T}^d)\), and \(w \in L^\infty (\mathbb {T}^d,\mathbb {R}^d)\), we consider the mapping
Combining inequalities (18) and (19) (with \(m=m_\tau \)), we directly obtain that for all \(t \in [0,T]\), for all \(v \in L_{m}^2(\mathbb {T}^d,\mathbb {R}^d)\) with \(m=m_\tau (\cdot ,t)\),
The following lemma will enable us to express \(P_\tau (t)\) and \(v_\tau (\cdot ,t)\) as functions of \(m_\tau (\cdot ,t)\) and \(u_\tau (\cdot ,t)\). The key idea is, roughly speaking, to prove the existence and uniqueness of a minimizer to \(J(\cdot ;t,m,w)\).
Lemma 5
For all \(t \in [0,T]\), for all \(m \in \mathcal {D}_1(\mathbb {T}^d)\), for all \(R > 0\), and for all \(w \in L^\infty (\mathbb {T}^d,\mathbb {R}^d)\) such that \(\Vert w \Vert _{L^\infty (\mathbb {T}^d,\mathbb {R}^d)} \le R\), there exists a unique pair \((v,P) \in L^\infty (\mathbb {T}^d,\mathbb {R}^d) \times \mathbb {R}^k\), such that
The pair (v, P) is then denoted \((\mathbf {v}(t,m,w),\mathbf {P}(t,m,w))\). Moreover, we have
where the constant C is independent of t, m, and w (but depends on R).
Proof
If the pair (v, P) satifies (20), then
One can easily check that for proving the existence and uniqueness of a pair (v, P) satisfying (20), it is sufficient to prove the existence and uniqueness of \(v \in L^\infty (\mathbb {T}^d,\mathbb {R}^d)\) satisfying (22). For future reference, let us observe that by (6), relation (22) is equivalent to
Step 1 existence and uniqueness of a minimizer of \(J(\cdot ;t,m,w)\).
In view of (A1), \(v \mapsto \int _{\mathbb {T}^d} L(v)m \; \mathrm {d} x\) is strongly convex over \(L_m^2(\mathbb {T}^d,\mathbb {R}^d)\). Since the sum of a l.s.c. convex function and of a l.s.c. strongly convex function is l.s.c. and strongly convex, so is the function \(J(\cdot ;t,m,w)\). Thus, it possesses a unique minimizer \(\bar{v}\) in \(L_m^2(\mathbb {T}^d,\mathbb {R}^d)\). We obtain
so that \(\Vert \bar{v}\Vert ^2_{L_m^2(\mathbb {T}^d,\mathbb {R}^d)} \le C\), with C independent of t, m, and w, but depending on R, as all constants C used in the proof.
Step 2 existence of \(\mathbf {v}(t,m,w)\) and a priori bound.
One can check that the mapping \(\delta v \in L^\infty (\mathbb {T}^d,\mathbb {R}^d) \mapsto J(\bar{v}+ \delta v;t,m,w)\) is differentiable. Since \(\bar{v}\) is optimal, the derivative of the above mapping is null at \(\delta v=0\) and thus
for a.e. \(x \in \mathbb {T}^d\). Using then the equivalence of (22) and (23), we obtain that
for a.e. \(x \in \mathbb {T}^d\). Consider now the measurable function v defined by
for a.e. \(x \in \mathbb {T}^d\). The two functions v and \(\bar{v}\) may not be equal for a.e. x if \(m(x)=0\) on a subset of \(\mathbb {T}^d\) of non-zero measure. Still they are equal in \(L_m^2(\mathbb {T}^d,\mathbb {R}^d)\), which ensures in particular that \({\textstyle \int }\phi (x',t) \bar{v}(x') m(x') \, \mathrm {d} x' = {\textstyle \int }\phi (x',t) {v}(x') m(x') \, \mathrm {d} x'\) and finally that v satisfies (22) and lies in \(L^\infty (\mathbb {T}^d,\mathbb {R}^d)\), as a consequence of the continuity of \(H_p\) (proved in Lemma 1). We also have that \(\Vert \bar{v} \Vert _{L_m^2(\mathbb {T}^d,\mathbb {R}^d)}= \Vert v \Vert _{L_m^2(\mathbb {T}^d,\mathbb {R}^d)} \le C\), by (24). Using the Cauchy–Schwarz inequality and assumption (A6), we obtain that \(|{\textstyle \int }\phi v m| \le C\). We obtain then with assumption (A4) that for \(P= \varPsi ( {\textstyle \int }\phi v m)\), we have \(|P| \le C\). Using assumption (A6) and the continuity of \(H_p\), we finally obtain that \(\Vert v \Vert _{L^\infty (\mathbb {T}^d,\mathbb {R}^d)} \le C\). Thus the bound (21) is satisfied.
Step 3 uniqueness of \(\mathbf {v}(t,m,w)\).
Let \(v_1\) and \(v_2 \in L^\infty (\mathbb {T}^d,\mathbb {R}^d)\) satisfy (22). Then \(DJ(v_i;t,m,w)= 0\), proving that \(v_1\) and \(v_2\) are minimizers of \(J(\cdot ;t,m,w)\) and thus are equal in \(L_m^2(\mathbb {T}^d,\mathbb {R}^d)\). Therefore \({\textstyle \int }\phi (x',t) v_1(x') m(x') \; \mathrm {d} x' = {\textstyle \int }\phi (x',t) v_2(x') m(x') \; \mathrm {d} x'\) and finally that \(v_1= v_2\), by (22). \(\square \)
5 Regularity Results for the Auxiliary Mappings
We provide in this section some regularity results for the mappings \(\mathbf {v}\) and \(\mathbf {P}\). We begin by proving that \(\mathbf {P}(\cdot ,\cdot ,\cdot )\) is locally Hölder continuous. For this purpose, we perform a stability analysis of the optimality condition (23).
Lemma 6
Let \(t_1\) and \(t_2 \in [0,T]\), let \(w_1\) and \(w_2 \in L^\infty (\mathbb {T}^d,\mathbb {R}^d)\), let \(m_1\) and \(m_2 \in \mathcal {D}_1(\mathbb {T}^d)\). Let \(R>0\) be such that \(\Vert w_i \Vert _{L^\infty (\mathbb {T}^d,\mathbb {R}^d)} \le R\), for \(i=1,2\). Then, there exist a constant \(C>0\) and an exponent \(\alpha \in (0,1)\), both independent of \(t_1\), \(t_2\), \(w_1\), \(w_2\), \(m_1\), and \(m_2\) but depending on R, such that
Proof
Note that all constants \(C>0\) and all exponents \(\alpha \in (0,1)\) involved below are independent of \(t_1\), \(t_2\), \(w_1\), \(w_2\), \(m_1\), and \(m_2\). They are also independent of \(x \in \mathbb {T}^d\) and \(\varepsilon > 0\). For \(i=1,2\), we set \(v_i= \mathbf {v}(t_i,m_i,w_i)\) and \(\phi _i= \phi (\cdot ,t_i) \in L^\infty (\mathbb {T}^d)\). By (21), we have
By the optimality condition (23), we have that
Consider the difference of (27) for \(i=2\) with (27) for \(i=1\). Integrating with respect to x the scalar product of the obtained difference with \(v_2m_2 - v_1m_1\), we obtain that \((a_1) + (a_2) + (a_3)= 0\), where
We look for a lower estimate of these three terms. Let us mention that the term \(v_2 m_2 - v_1 m_1\), appearing in the three terms, will be estimated only at the end.
Estimation from below of \((a_1)\). We have \((a_1)= (a_{11}) + (a_{12})\), where
By monotonicity of \(\varPsi \), we have that
Let us consider \((a_{11})\). We set
so that \((a_{11})= \int _{\mathbb {T}^d} \langle \xi , v_2 m_2 - v_1 m_1 \rangle \, \mathrm {d} x\). Using assumption (A6), one can check that \(|\varPsi _i | \le C\) and that \(\big | \varPsi _2 - \varPsi _1 \big | \le C|t_2- t_1|^\alpha \). Since \(\xi = (\phi _2-\phi _1)^\intercal \varPsi _2 + \phi _1^\intercal (\varPsi _2-\varPsi _1)\), we obtain with assumption (A6) again that
and further with Young’s inequality that
Estimation from below of \((a_2)\). We have \((a_2)= (a_{21}) + (a_{22}) + (a_{23})\), where
As a consequence of (26), assumption (A6), and Young’s inequality, we have
By (26) and assumption (A6), \(| L_v(t_1,x,v_i(x)) | \le C\), therefore
Finally, since \(m_1 \ge 0\) and by assumption (A1), we have
Estimation from below of \((a_3)\). Using (29) and Young’s inequality, we obtain that
Conclusion. We have proved that
Let us estimate \(\Vert v_2 m_2 - v_1 m_1 \Vert _{L^1(\mathbb {T}^d;\mathbb {R}^d)}\). Using the Cauchy–Schwarz inequality, we obtain that
Injecting this inequality in (28) and taking \(\varepsilon = {1}/{3C}\), we obtain that
Let us prove (25). We have
Therefore, using assumption (A6) and (30), we obtain that
Inequality (25) follows, using assumption (A6). The lemma is proved. \(\square \)
Given \(m \in L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\) and \(w \in L^\infty (Q)\), we consider the Nemytskii operators associated with \(\mathbf {v}\) and \(\mathbf {P}\), that we still denote by \(\mathbf {v}\) and \(\mathbf {P}\) without risk of confusion:
for all \((x,t) \in Q\). We use now Lemma 6 to prove regularity properties of the Nemytskii operators \(\mathbf {v}\) and \(\mathbf {P}\). We recall that \(X = \big ( W^{2,1,p}(Q) \big )^2\).
Lemma 7
For all \(R>0\), the mapping
and the mapping
are both Hölder continuous, that is, there exist \(\alpha \in (0,1)\) and \(C>0\) such that
for all \(m_1\) and \(m_2 \in L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\), for all \(w_1\) and \(w_2 \in B(L^\infty (Q,\mathbb {R}^d),R)\), and for all \(u_1\) and \(u_2\) in \(B(W^{2,1,p}(Q),R)\).
Proof
The Hölder continuity of the first mapping is a direct consequence of Lemma 6. As a consequence, the mapping
is Hölder continuous. Using then the relations
and the Hölder continuity of \(H_p\), \(H_{px}\), and \(H_{pp}\) on bounded sets (Lemma 1), we obtain that the second mapping is Hölder continuous. \(\square \)
Remark 2
As a consequence of Lemma 7, the images of the mappings given by (31) and (32) are bounded. This fact will be used in the steps 3 and 5 of the proof of Proposition 1.
Lemma 8
Let \(R>0\) and \(\beta \in (0,1)\). Then, there exists \(\alpha \in (0,1)\) and \(C>0\) such that for all \(u \in B(W^{2,1,p}(Q),R)\) and for all \(m \in B(\mathcal {C}^{\beta }(Q),R) \cap L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\), \(\Vert \mathbf {P}(m,\nabla u) \Vert _{\mathcal {C}^\alpha (0,T;\mathbb {R}^k)} \le C\).
Proof
We recall that by Lemma 12, \(\Vert \nabla u \Vert _{\mathcal {C}^{\alpha }(Q,\mathbb {R}^d)} \le C \Vert u \Vert _{W^{2,1,p}(Q)}\). We obtain then the bound on \(\Vert \mathbf {P}(m,\nabla u) \Vert _{\mathcal {C}^\alpha (0,T;\mathbb {R}^k)}\) with Lemma 6. \(\square \)
Lemma 9
Let \(R>0\) and \(\beta \in (0,1)\). There exist \(\alpha \in (0,1)\) and \(C>0\) such that for all \(u \in B(\mathcal {C}^{2+\beta ,1+\beta /2}(Q),R)\) and for all \(m \in B(\mathcal {C}^\beta (Q),R) \cap L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\),
Proof
The result follows from relations (33), Lemma 8, and from the Hölder continuity of \(H_p\), \(H_{px}\), and \(H_{pp}\) on bounded sets. \(\square \)
6 A Priori Estimates for Fixed Points
Proposition 1
There exist a constant \(C>0\) and an exponent \(\alpha \in (0,1)\) such that for all \(\tau \in [0,1]\), for all \((u_\tau ,m_\tau ,v_\tau ,P_\tau ) \in X'\) satisfying (MFGC\(_\tau \)),
Proof
Let us fix \(\tau \in [0,1]\) and \((u_\tau ,m_\tau ,v_\tau ,P_\tau ) \in X'\) satisfying (MFGC\(_\tau \)). All constants C and all exponents \(\alpha \in (0,1)\) involved below are independent of \((u_\tau ,m_\tau ,v_\tau ,P_\tau )\) and \(\tau \). Let us recall that \(\tilde{f}_\tau \in L^\infty (Q)\) has been defined in Lemma 4 by \(\tilde{f}_\tau (x,t)= f(x,t,m_\tau (t))\).
Step 1 \(\Vert P_\tau \Vert _{L^2(0,T;\mathbb {R}^k)} \le C\).
Let \(v^0=0\) and let \(m^0\) be the solution to \(\partial _t m^0 - \sigma \varDelta m^0= 0\), \(m^0(x,0) = m_0 (x)\). By Lemma 4, \(B(m_\tau ,v_\tau ;\tilde{f}_\tau ) \le B(m^0,v^0;\tilde{f}_\tau )\). Since \(\Vert \phi \Vert _{L^\infty (Q,\mathbb {R}^{k \times d})} \le C\), we have for all \(\varepsilon >0\) and for all \(t \in [0,T]\) that
by the Cauchy–Schwarz inequality and Young’s inequality. The constant C is also independent of \(\varepsilon \). Using then the lower bounds (8) and (9) and assumptions (A5) and (A8), we obtain that
Taking \(\varepsilon = 1 / (2C^2)\), we deduce that \(\iint _Q |v_\tau |^2 m_\tau \, \mathrm {d} x \, \mathrm {d} t \le C\). Using then assumption (A4), the boundedness of \(\phi \), the Cauchy–Schwarz inequality and the estimate obtained previously, we deduce that
Step 2 \(\Vert u_\tau \Vert _{L^\infty (Q)} \le C\), \(\Vert \nabla u_\tau \Vert _{L^\infty (Q,\mathbb {R}^d)} \le C\).
The argument is classical. We have that \(u_\tau \) is the unique solution to the HJB equation (i) (MFGC\(_\tau \)). It is therefore the value function associated with the following stochastic optimal control problem:
where \(J_\tau (x,t,\alpha )\) is defined by
and \((X_s)_{s \in [t,T]}\) is the solution to the stochastic dynamic \(\mathrm {d} X_s = \tau \alpha _s \mathrm {d} s + \sqrt{2\sigma } \mathrm {d} B_s, \; X_t = x\). Here, \(L_{\mathbb {F}}^2(t,T;\mathbb {R}^d)\) denotes the set of stochastic processes on (t, T), with values in \(\mathbb {R}^d\), adapted to the filtration \(\mathbb {F}\) generated by the Brownian motion \((B_s)_{s \in [0,T]}\), and such that \(\mathbb {E}\big [ \int _t^T |\alpha (s)|^2 \; \mathrm {d} s \big ] < \infty \). Then, the boundedness of \(u_\tau \) from above can be immediately obtained by choosing \(\alpha = 0\) in (35) and using the boundedness of g. We can as well bound \(u_\tau \) from below since for all \((x,s) \in Q\) and for all \(\alpha \in \mathbb {R}^d\), we have
for some constant C independent of (x, s), \(\alpha \), and \(P_\tau (s)\). We already know from the previous step that \( \Vert P_\tau \Vert _{L^2(0,T;\mathbb {R}^k)} \le C\). So we can conclude that \(u_\tau \) is also bounded from below, and thus \(\Vert u_\tau \Vert _{L^\infty (Q)} \le C\). We also deduce from the above inequality that for all \(\alpha \in L_{\mathbb {F}}^2(t,T;\mathbb {R}^d)\),
Let us bound \(\nabla u_\tau \). Choose \(\varepsilon \in (0,1)\). For arbitrary (x, t), take an \(\varepsilon \)-optimal stochastic optimal control \({\tilde{\alpha }}\) for (35). We can deduce from the boundedness of the map \(u_\tau \) and inequality (36) that
where C is independent of \((\tau ,x,t)\) and \(\varepsilon \). Let \(y \in \mathbb {T}^d\). Set
then obviously \(\mathrm {d} Y_s = {\tilde{\alpha }}_s \mathrm {d} s + \sqrt{2\sigma } \mathrm {d} B_s , \; Y_t = y\). We have
Therefore, \(u_\tau (y,t) - u_\tau (x,t) \le \varepsilon + |(a)| + |(b)| + |(c)| + |(d)|\), where (a), (b), (c), (d) are given by
First, we have
as a consequence of assumption (A3) and (37). Then, using assumption (A6), (34), and (37), we obtain
By assumption (A8), \(|(c)| \le \mathbb {E} \big [ |g(Y_T)-g(X_T)| \big ] \le C |y-x|\). Finally, since \(\tilde{f}_\tau \) is a Lipschitz function (by assumption (A7)),
Letting \(\varepsilon \rightarrow 0\), we obtain that \(u_\tau (y,t) - u_\tau (x,t) \le C |y-x|\). Exchanging x and y, we obtain that \(u_\tau \) is Lipschitz continuous with modulus C and finally that \(\Vert \nabla u_\tau \Vert _{L^\infty (Q,\mathbb {R}^d)} \le C\).
Step 3 \(\Vert P_\tau \Vert _{L^\infty (0,T;\mathbb {R}^k)} \le C\).
By Lemma 3, \(m_\tau \in L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\). We have that \(\Vert \nabla u_\tau \Vert _{L^\infty (Q,\mathbb {R}^d)} \le C\) and \(P_\tau = \mathbf {P}(m_\tau ,\nabla u_\tau )\). The bound on \(\Vert P_\tau \Vert _{L^\infty (0,T;\mathbb {R}^k)}\) follows then from Lemma 7 and Remark 2.
Step 4 \(\Vert u_\tau \Vert _{W^{2,1,p}(Q)} \le C\).
By assumption (A6), \(\phi \) is bounded. We have proved that \(\Vert P_\tau \Vert _{L^\infty (0,T;\mathbb {R}^k)} \le C\) and by Lemma 1, H is continuous. Thus, \(\Vert H(\nabla u_\tau + \phi ^\intercal P_\tau ) \Vert _{L^\infty (Q)} \le C\). By assumption (A5), \(\Vert \tau \tilde{f}_\tau \Vert _{L^\infty (Q)} \le C\). It follows that \(u_\tau \), as the solution to the HJB equation (i) (MFGC\(_\tau \)), is the solution to a parabolic equation with bounded coefficients. Thus, by Theorem 6, \(\Vert u_\tau \Vert _{W^{2,1,p}(Q)} \le C\). We also obtain with Lemma 12 that \(\Vert u_\tau \Vert _{\mathcal {C}^\alpha (Q)} \le C\) and \(\Vert \nabla u_\tau \Vert _{\mathcal {C}^\alpha (Q,\mathbb {R}^d)} \le C\).
Step 5 \(\Vert v_\tau \Vert _{L^\infty (Q,\mathbb {R}^d)} \le C\), \(\Vert D_x v_\tau \Vert _{L^p(Q,\mathbb {R}^{d \times d})} \le C\).
We have proved that \(v_\tau = \mathbf {v}(m_\tau ,\nabla u_\tau )\) and \(\Vert u_\tau \Vert _{W^{2,1,p}(Q)} \le C\). The estimate follows directly with Lemma 7 and Remark 2.
Step 6 \(\Vert m_\tau \Vert _{\mathcal {C}^\alpha (Q)} \le C\).
The Fokker–Planck equation can be written in the form of a parabolic equation with coefficients in \(L^p\): \(\partial _t m_{\tau } - \sigma \varDelta m_\tau + \tau \langle v_\tau , \nabla m_\tau \rangle + \tau m_\tau \text {div}(v_\tau )= 0\), since \(\Vert D_x v_\tau \Vert _{L^p(Q,\mathbb {R}^{d \times d})} \le C\). Combining Theorem 4 and Lemma 12, we get that \(\Vert m_\tau \Vert _{\mathcal {C}^\alpha (Q)} \le C\).
Step 7 \(\Vert P_\tau \Vert _{\mathcal {C}^\alpha (0,T;\mathbb {R}^k)} \le C\).
We already know that \(\Vert u_\tau \Vert _{W^{2,1,p}(Q)} \le C\), that \(\Vert m_\tau \Vert _{\mathcal {C}^\alpha (Q)} \le C\), and that \(m_\tau \in L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\). Thus Lemma 8 applies and yields that \(\Vert P_\tau \Vert _{\mathcal {C}^\alpha (0,T;\mathbb {R}^k)} \le C\).
Step 8 \(\Vert u_\tau \Vert _{\mathcal {C}^{2+\alpha ,1+ \alpha /2}(Q)} \le C\).
We have proved that \(\Vert \nabla u_\tau \Vert _{\mathcal {C}^\alpha (Q,\mathbb {R}^d)} \le C\) and \(\Vert P_\tau \Vert _{\mathcal {C}^\alpha (0,T;\mathbb {R}^k)} \le C\). Moreover, we have assumed that \(\phi \) is Hölder continuous and know that H is Hölder continuous on bounded sets. It follows that \(\Vert H(\nabla u_\tau + \phi ^\intercal P_\tau ) \Vert _{\mathcal {C}^\alpha (Q)} \le C\). It follows from assumption (A7) that \(\tau \tilde{f}_\tau \) is Hölder continuous. Since \(g \in \mathcal {C}^{2+\alpha }(\mathbb {T}^d)\), we finally obtain that \(\Vert u_\tau \Vert _{\mathcal {C}^{2+\alpha ,1+ \alpha /2}(Q)} \le C\), by Theorem 7.
Step 9 \(\Vert v_\tau \Vert _{\mathcal {C}^\alpha (0,T;\mathbb {R}^{d})} \le C\) and \(\Vert D_x v_\tau \Vert _{\mathcal {C}^\alpha (0,T;\mathbb {R}^{d \times d})} \le C\).
We have \(\Vert u_\tau \Vert _{\mathcal {C}^{2+\alpha ,1+\alpha /2}(Q)} \le C\) and \(\Vert m_\tau \Vert _{\mathcal {C}^\alpha (Q)} \le C\). Thus Lemma 9 applies and the announced estimates hold true.
Step 10 \(\Vert m_\tau \Vert _{\mathcal {C}^{2+ \alpha , 1 + \alpha /2}(Q)} \le C\).
A direct consequence of Step 9 is that \(m_\tau \) is the solution to a parabolic equation with Hölder continuous coefficients. Therefore \(\Vert m_\tau \Vert _{\mathcal {C}^{2+\alpha ,1 + \alpha /2}(Q)} \le C\), by Theorem 7, which concludes the proof of the proposition. \(\square \)
7 Application of the Leray–Schauder Theorem
Proof
(Theorem 1) Step 1 construction of \(\mathcal {T}\).
Let us define the mapping \(\mathcal {T} :X \times [0,1] \rightarrow X\) which is used for the application of the Leray–Schauder theorem. A difficulty is that the auxiliary mappings \(\mathbf {P}\) and \(\mathbf {v}\) are only defined for \(m \in L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\). Therefore we need a kind of projection operator on this set. Note that \(\int _{\mathbb {T}^d} 1 \, \mathrm {d} x = 1\). We consider the mapping
defined by
where \(m_+(x,t)= \max (0,m(x,t))\). For checking that \(\rho (m) \in L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\), we suggest to consider the two cases: \({\textstyle \int }m_+(y,t) \; \mathrm {d} y < 1\) and \({\textstyle \int }m_+(y,t) \; \mathrm {d} y \ge 1\) separetely. The following properties can be easily checked:
-
For all \(m \in L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\), \(\rho (m)=m\).
-
The mapping \(\rho \) is locally Lipschitz continuous, from \(L^\infty (Q)\) to \(L^\infty (Q)\).
-
For all \(\alpha \in (0,1)\), there exists a constant \(C>0\) such that if \(m \in \mathcal {C}^\alpha (Q)\), then \(\rho (m) \in \mathcal {C}^\alpha (Q)\) and \(\Vert \rho (m) \Vert _{\mathcal {C}^{\alpha }(Q)} \le C \Vert m \Vert _{\mathcal {C}^{\alpha }(Q)}\).
For a given \((u,m,\tau ) \in X \times [0,1]\), the pair \((\tilde{u},\tilde{m})= \mathcal {T}(u,m,\tau )\) is defined as follows: \(\tilde{u}\) is the solution to
and \(\tilde{m}\) is the solution to
It directly follows from the definition of \(\mathcal {T}\) that \(\mathcal {T}(u,m,0)\) is constant, as required by the Leray–Schauder theorem.
Step 2 a priori bound.
Let \(\tau \in [0,1]\) and let \((u_\tau ,m_\tau )\) be such that \((u_\tau ,m_\tau )= \mathcal {T}(u_\tau ,m_\tau ,\tau )\). Then, by Lemma 3, \(m_\tau \in L^\infty (0,T;\mathcal {D}_1(\mathbb {T}^d))\). Thus, \(m_\tau = \rho (m_\tau )\) and finally, by Lemma 5, the quadruplet \((u_\tau ,m_\tau ,P_\tau ,v_\tau )\), with \(P_\tau = \mathbf {P}(m_\tau ,\nabla u_\tau )\) and \(v_\tau = \mathbf {v}(m_\tau ,\nabla u_\tau )\), is a solution to (MFGC\(_\tau \)). We directly conclude with Proposition 1 that \(\Vert (u_\tau ,m_\tau ) \Vert _X \le C\), where C is independent of \(\tau \).
Step 3 continuity of \(\mathcal {T}\).
Using the continuity of \(\rho \), Lemma 7, the Hölder continuity of H, and assumption (A7), we obtain that the mappings
are continuous. By Theorem 6, the solution to a parabolic equation of the form (51), with b and c null (in \(W^{2,1,p}(Q)\)) is a continuous mapping of the right-hand side (in \(L^p(Q)\)). Thus, \(\tilde{u} \in W^{2,1,p}(Q)\) depends in a continuous way on \(\tau H(\nabla u + \phi ^\top \mathbf {P}(\rho (m),\nabla u))\) and therefore \(\tilde{u}\) depends in a continuous way on \((\tau ,u,m)\) by composition. Again, by Theorem 6, \(\tilde{m} \in W^{2,1,p}(Q)\) depends in a continuous way on \(\tau \text {div}(\mathbf {v}(\rho (m),\nabla \tilde{u})m)\) and therefore depends in a continuous way on \((\tau ,u,m)\).
Step 4 compactness of \(\mathcal {T}\).
Let \(R>0\), let \((u,m) \in B(X,R)\). We have \(\Vert \rho (m) \Vert _{\mathcal {C}^{\alpha }(Q)} \le C\), where C is independent of (u, m) (but depends on R). As a consequence of assumption (A7), and since H is Hölder continuous on bounded sets, we have
where \(C>0\) and \(\alpha \in (0,1)\) are both independent of (u, m) (but depend on R). It follows then that \(\Vert u \Vert _{\mathcal {C}^{2+\alpha ,1+\alpha /2}(Q)} \le C\) by Theorem 7. Using Lemma 9, we deduce then that
and finally obtain that \(\Vert m \Vert _{\mathcal {C}^{2+\alpha ,1+ \alpha /2}(Q)} \le C\), by Theorem 7 again. The compactness of \(\mathcal {T}\) follows, since \(\mathcal {C}^{2+\alpha ,1+\alpha /2}(Q)\) is compactly embedded in \(W^{2,1,p}(Q)\), by the Arzelà–Ascoli theorem.
Step 5 Conclusion.
The existence of a fixed point (u, m) to \(\mathcal {T}(\cdot ,\cdot ,1)\) follows. With the same arguments as those of Step 2, we obtain that \((u,m,\mathbf {P}(m,\nabla u),\mathbf {v}(m,\nabla u))\) is a solution to (MFGC\(_\tau \)) with \(\tau =1\) and that (15) holds, by Proposition 1. \(\square \)
8 Uniqueness and Duality
In this section we prove the uniqueness of the solution (u, m, v, P) to (MFGC). We also prove that (P, v) is the solution to a dual problem to (17). Both results are obtained under the following additional monotonicity assumption of f: There exists a measurable mapping \(F(t,m) :[0,T]\times \mathcal {D}_1(\mathbb {T}^d)\rightarrow \mathbb {R}\) such that
for all \(m_1\) and \(m_2 \in \mathcal {D}_1(\mathbb {T}^d)\) and for a.e. t. Thus, \(F(t,\cdot )\) is a supremum of the exact affine minorants appearing in the above right-hand side, and is therefore a convex function of m.
Remark 3
-
1.
It follows from (40) that f is monotone:
$$\begin{aligned} \int _{ \mathbb {T}^d} (f(x,t,m_2)- f(x,t,m_2)) (m_2(x) - m_1(x)) \; \mathrm {d} x \ge 0, \end{aligned}$$(41)for all \(m_1\) and \(m_2 \in \mathcal {D}_1(\mathbb {T}^d)\) and for a.e. t. Conversely, (40) holds true if (41) is satisfied and if F is a primitive of f(., t, .) in the sense that
$$\begin{aligned} F(t,m_2) - F(t,m_1) = \int _{0}^{1} \int _{\mathbb {T}^d} f(x,t, sm_2 + (1-s)m_1) (m_2(x) - m_1(x)) \; \mathrm {d} s. \end{aligned}$$We refer to [5, Proposition 1.2] for a further characterization of functions f deriving from a potential.
-
2.
Consider the mapping \(f_K\) proposed in Lemma 2. Assume that for all \((x,t) \in Q\), \(K(x,t,\cdot )\) is non-decreasing and consider the function \(\mathcal {K}\) defined by \(\mathcal {K}(x,t,w) := \int _0^w K(x,t,w') \; \mathrm {d} w'\), for \((x,t,w) \in Q \times [-C_2,C_2]\). Then inequality (40) holds true with \(F_K\) defined by
$$\begin{aligned} F_K(t,m)= \int _{\mathbb {T}^d} \mathcal {K} (x,t,m * \varphi (x)) \; \mathrm {d} x. \end{aligned}$$Indeed, since \(\mathcal {K}\) is convex in its third argument, we have
$$\begin{aligned}&F_K(t,m_2)-F_K(t,m_1) = \int _{\mathbb {T}^d} \mathcal {K}(x,t,m_2 * \varphi (x)) - \mathcal {K}(x,t,m_1 * \varphi (x)) \; \mathrm {d} x \\&\quad \ge \int _{\mathbb {T}^d} K(x,t,m_1* \varphi (x))((m_2-m_1)*\varphi )(x) \; \mathrm {d} x \\&\quad = \int _{\mathbb {T}^d} (K(\cdot ,t,m_1*\varphi (\cdot ))* \tilde{\varphi })(x) (m_2(x) - m_1(x)) \; \mathrm {d} x \\&\quad = \int _{\mathbb {T}^d} f_K(x,t,m)(m_2(x)-m_1(x)) \; \mathrm {d} x, \end{aligned}$$as was to be proved.
Without loss of generality, we can assume that \(F(t,m_0)=0\) for a.e. \(t \in (0,T)\). It can then be easily deduced from assumption (A5) and (40) that there exists a constant C such that
Let us consider the potential \(B :W^{2,1,p}(Q) \times L^\infty (Q;\mathbb {R}^k) \rightarrow \mathbb {R}\), defined by
Proposition 2
There exists a unique solution \((u,m,v,P) \in X'\) to (MFGC). Moreover, the pair (m, v) is the solution to the following optimal control problem
Proof
Let \((u,m,v,P) \in X'\) be a solution to (MFGC). Let us prove that (m, v) is a solution to (44). Let \((\hat{m},\hat{v})\) be a feasible pair. Denoting \(\tilde{f}(x,t)= f(x,t,m(t))\), we have
The two terms in the right-hand side are both nonnegative, as a consequence of Lemma 4 and assumption (40), respectively.
It remains to prove the uniqueness of the solution to (MFGC). Let us prove first a classical property: There exists a constant \(C>0\) such that for all \((x,t) \in Q\), for all \(p \in \mathbb {R}^d\) and for all \(v \in \mathbb {R}^d\),
Let us set \(\bar{v}= - H_p(x,t,p)\). For a fixed triple (x, t, p), we have \(H(x,t,p)= - \langle p,\bar{v} \rangle - L(x,t,\bar{v})\). Moreover, \(L_v(x,t,\bar{v})= -p\) and thus by (A1),
Inequality (45) follows.
Let \((u_1,m_1,v_1,P_1)\) and \((u_2,m_2,v_2,P_2)\) be two solutions to (MFGC) in \(X'\). We obtain with inequality (45) that
Proceeding then exactly like in the proof of Lemma 4, we arrive at the following inequality:
We also have that \(B(m_1,v_1)-B(m_2,v_2) \ge 0\), thus \(\iint _Q |v_2 - v_1 |^2 m_2 \; \mathrm {d} x \; \mathrm {d} t= 0\). As a consequence, \((v_2-v_1)m_2= 0\), since \(m_2 \ge 0\). We obtain then that
Let us set \(m= m_2- m_1\). Using relation (46), we obtain that m is the solution to the following parabolic equation: \(\partial _t m - \sigma \varDelta m + \text {div}(v_1 m)= 0\), \(m(x,0)=0\). Therefore \(m=0\) and \(m_2= m_1\). We already know that \(v_2m_2= v_1m_2\), we deduce then that \(v_2m_2= v_1m_1\). We obtain further with (iii) that \(P_1= P_2\), then with (i) that \(u_1= u_2\) and finally with (iv) that \(v_1= v_2\), which concludes the proof. \(\square \)
We finish this section with a duality result. For \(\gamma \in L^\infty (\mathbb {T}^d)\), we recall that the convex conjugate of \(F(t,\cdot )\) is defined by
It directly follows from the above definition that \(|F^*(t,\gamma )| \le \Vert \gamma \Vert _{L^\infty (\mathbb {T}^d)} + C\), where C is the constant obtained in (42) and thus for \(\gamma \in L^\infty (Q)\), the integral \(\int _0^T F^*(t,\gamma (\cdot ,t)) \; \mathrm {d} t\) is well-defined.
Consider the dual criterion \(D :(u,P,\gamma ) \in W^{2,1,p}(Q) \times L^\infty (0,T;\mathbb {R}^k) \times L^\infty (Q) \mapsto D(u,p,\gamma ) \in \mathbb {R}\cup \{ - \infty \}\), defined by
The function \(\varPhi ^*\) is the convex conjugate of \(\varPhi \) with respect to its second argument. Since \(\varPhi (t,0)=0\), we have that \(\varPhi ^*(t,\cdot ) \ge 0\) and thus the first integral is well-defined in \(\mathbb {R}\cup \{ \infty \}\).
Lemma 10
Let \((\bar{u},\bar{m},\bar{v},\bar{P})\) be the solution to (MFGC). Let \(\tilde{f}\) be defined by \(\tilde{f}(x,t)= f(x,t,\bar{m}(t))\). Then, \((\bar{u},\bar{P},\tilde{f})\) is a solution to the following problem:
Moreover, for all solutions \((u,P,\gamma )\) to the dual problem, \(P=\bar{P}\). If in addition, \(\gamma = \tilde{f}\) and the above inequalities hold as equalities, then \(u= \bar{u}\).
Proof
For all \(t \in [0,T]\), we have
with
We also have that
where
Integrating by parts (in time), we obtain that
where
Integrating by parts (in space), we further obtain that
where
Combining (48), (49) and (50) together, we finally obtain that
The five terms (a), (b), (c), (d), (e) are non-positive and equal to zero if \((u,P,\gamma )=(\bar{u},\bar{P},\tilde{f})\), as can be easily verified. This proves the optimality of \((\bar{u},\bar{P},\tilde{f})\). Moreover, since \(\varPhi \) is differentiable (with gradient \(\varPsi \)), the term (a) is null if and only if \(P(t)= \varPsi ({\textstyle \int }\phi \bar{v} \bar{m})= \bar{P}(t)\), for a.e. \(t \in [0,T]\). Therefore, for all optimal solutions \((u,P,\gamma )\), \(P= \bar{P}\). If moreover \(\gamma = \tilde{f}\) and the inequality constraints in (47) hold as equalities, then (since the HJB equation has a unique solution) \(u= \bar{u}\), which concludes the proof. \(\square \)
Remark 4
It is of interest to check when the density m(x, t) is a.e. positive, since this is clearly a necessary condition for the uniqueness of the solution of (44). We note that a sufficient condition for the positivity of m is given in [21, Proposition 3.10].
9 Conclusion
The existence and uniqueness of a classical solution to a mean field game of controls have been demonstrated. A particularly important aspect of the analysis is the fact that the equations (iii) and (iv) (MFGC), encoding the coupling of the agents through the controls, are equivalent to the optimality system of a ‘static’ convex problem. This observation enabled us to eliminate the variables v and P from the coupled system.
The analysis done in this article can be extended in different ways. A more complex interaction between the agents could be considered. For example, it would be possible to replace equations (iii) and (iv) by the following ones:
assuming that \(\varphi \) is convex with respect to v and \(\varPsi \ge 0\). For a fixed \(t \in [0,T]\), this system is equivalent to the optimality system associated with the following convex problem:
Another possibility of extension of our analysis would be to add convex constraints on the control variable.
Future research will aim at exploiting the potential structure of the problem, which can be used to solve it numerically and to prove the convergence of learning procedures, as was done in [5].
References
Acciaio, B., Backhoff-Veraguas, J., Carmona, R.: Extended mean field control problems: stochastic maximum principle and transport perspective. ArXiv preprint (2018)
Alasseur, C., Ben Tahar, I., Matoussi, A.: An extended mean field game for storage in smart grids. ArXiv preprint (2018)
Bertucci, C., Lasry, J.M., Lions, P.L.: Some remarks on mean field games. Commun. Part. Diff. Eq. 44(3), 205–227 (2019)
Cardaliaguet, P.: Long time average of first order mean field games and weak KAM theory. Dyn. Games Appl. 3(4), 473–488 (2013)
Cardaliaguet, P., Hadikhanloo, S.: Learning in mean field games: the fictitious play. ESAIM Control Optim. Calculus Var. 23(2), 569–591 (2017)
Cardaliaguet, P., Lehalle, C.-A.: Mean field game of controls and an application to trade crowding. Math. Financ. Econ. 12(3), 335–363 (2018)
Carmona, R., Delarue, F.: Probabilistic theory of mean field games with applications. I. Probability Theory and Stochastic Modelling. Springer, Cham (2018)
Carmona, R., Lacker, D.: A probabilistic weak formulation of mean field games and applications. Ann. Appl. Prob. 25(3), 1189–1231 (2015)
Chan, P., Sircar, R.: Fracking, renewables, and mean field games. SIAM Rev. 59(3), 588–615 (2017)
Couillet, R., Perlaza, S., Tembine, H., Debbah, M.: Electrical vehicles in the smart grid: a mean field game analysis. IEEE J. Sel. Areas Commun. 30(6), 1086–1096 (2012)
De Paola, A., Angeli, D., Strbac, G.: Distributed control of micro-storage devices with mean field games. IEEE Trans. Smart Grid 7(2), 1119–1127 (2016)
Gilbarg, D., Trudinger, N.S.: Elliptic partial differential equations of second order. Springer, New York (2015)
Gomes, D.A., Patrizi, S., Voskanyan, V.: On the existence of classical solutions for stationary extended mean field games. Nonlinear Anal. 99, 49–79 (2014)
Gomes, D. A., Saúde, J.: A mean field game approach to price formation in electricity markets. ArXiv preprint (2018)
Gomes, D.A., Voskanyan, V.K.: Extended deterministic mean-field games. SIAM J. Control Optim. 54(2), 1030–1055 (2016)
Graber, P.J., Bensoussan, A.: Existence and uniqueness of solutions for bertrand and cournot mean field games. Appl. Math. Optim. 77, 47–71 (2015)
Graber, P. J., Mouzouni, C.: Variational mean field games for market competition. ArXiv preprint (2017)
Graber, P. J., Mouzouni, C.: On mean field games models for exhaustible commodities trade. ESAIM Control Optim. Calc. Var., Forthcoming article
Ladyzhenskaia, O.A., Solonnikov, V.A., Ural’tseva, N.N.: Linear and quasi-linear equations of parabolic type. American Mathematical Society, Providence (1988)
Pham, H., Wei, X.: Bellman equation and viscosity solutions for mean-field stochastic control problem. ESAIM Control Optim. Calc. Var. 24(1), 437–461 (2018)
Porretta, A.: Weak solutions to Fokker-Planck equations and mean field games. Arch. Ration. Mech. Anal. 216(1), 1–62 (2015)
Acknowledgements
Open access funding provided by University of Graz. The authors want to thank an anonymous referee for his useful remarks. The first author acknowledges support from the FiME Lab (Institut Europlace de Finance). The first two authors acknowledges support from the PGMO project “Optimal control of conservation equations”, itself supported by iCODE (IDEX Paris-Saclay) and the Hadamard Mathematics LabEx.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix: A Priori Bounds for Parabolic Equations
Appendix: A Priori Bounds for Parabolic Equations
In this appendix we provide estimates for the following parabolic equation:
for different assumptions on b, c, h, and \(u_0\). The technique is based on the following idea. By standard parabolic estimates detailed below, (51) has a unique solution u in \(L^2(0,T; H^1(\mathbb {T}^d))\), that we may identify with a periodic function over \(\mathbb {R}^d\). Let \(\varphi :\mathbb {R}^d\rightarrow \mathbb {R}\) be of class \(C^\infty \), with value 1 in a neighbourhood of the closure of \(\mathbb {T}^d\), and with compact support in \(\varOmega := B(0,2)\). Set \(Q':=\varOmega \times (0,T)\). Then \(v := u\varphi \) is solution of
with \(v_0:= u_0\varphi \) and
Observe that the solution v of (52) is equal to 0 in a vicinity of \((\partial \varOmega ) \times (0,T)\), and hence, satisfies the homogeneous Neumann condition; this allows us to apply some results of [19].
Lemma 11
Let \(y \in W^{2,1,q}(Q')\), with \(q \in (1,\infty )\). Then \(y \in L^{q'}(Q')\) and \(\nabla y\in L^{q''}(Q')\), where
with continuous inclusion:
Proof
See [19, Lemma 3.3, page 80]. \(\square \)
Theorem 3
Let \(q\in (1,\infty )\), \(w_0\in W^{2-2/q,q}(\varOmega )\), and \(h \in L^q(Q')\). Then the heat equation
with homogeneous Neumann boundary condition on \(\partial \varOmega \times (0,T)\), has a unique solution in \(W^{2,1,q}(Q')\) that satisfies
Proof
See [19, Theorem IV.9.1, page 341]. \(\square \)
Theorem 4
Let \(p > d+2\). For all \(R>0\), there exists \(C>0\) such that for all \(u_0 \in W^{2-2/p,p}(\mathbb {T}^d)\), for all \(b \in L^p(Q,\mathbb {R}^d)\), for all \(c \in L^p(Q)\), for all \(h \in L^p(Q)\), satisfying
equation (51) has a unique solution u in \(W^{2,1,p}(Q)\) satisfying moreover \(\Vert u \Vert _{W^{2,1,p}(Q)} \le C\).
Proof
We first check that there is a solution in the standard variational setting with spaces \(H:=L^2(\mathbb {T}^d)\), \(V := H^1(\mathbb {T}^d)\). Let us show that, if \(y\in V\), then \(\langle b, \nabla y \rangle \) and cy belong to \(V^*\). By the Sobolev inclusion, \(V\subset L^{q_1}(\mathbb {T}^d)\), \(1/q_1=1/2-1/d\), with dense inclusion, so that \(V^*\subset L^{q_1}(\mathbb {T}^d)^* = L^{q_2}(\mathbb {T}^d)\), with \(1/q_2=1-1/q_1 = 1/2+1/d\). Now \( \langle b, \nabla y \rangle \in L^r(\mathbb {T}^d)\) with
so that \(\langle b, \nabla y \rangle \) belongs to \(V^*\). Similarly, \(c y \in L^r(\mathbb {T}^d)\) with
so that cy belongs to \(V^*\). So, (51) has a unique solution in the space
Then we easily check that \(h[u] \in L^{q_0}(Q')\), for some \(q_0\in (1,2)\). Then, by Theorem 3, \(v \in W^{2,1,q_0}(Q)\). We next compute by induction a finite sequence \((q_k)_{k=0,1,\ldots ,K}\) such that
The first element \(q_0\) has already been fixed and satifies \(v \in W^{2,1,q_0}(Q')\). If \(q_0 \ge d+2\), we can stop and set \(K=0\). Let \(k \in \mathbb {N}\), assume that \(q_k \in (1,d+2)\) and that \(v \in W^{2,1,q_k}(Q')\). Then v is solution of
where
We construct now \(q_{k+1}\) in such a way that \(h''[u] \in L^{q_{k+1}}(Q')\). Since \(v \in W^{2,1,q_k}(Q')\), we have that \(u \in W^{2,1,q_k}(Q)\) and thus by Lemma 11, \(\langle b, \nabla u\rangle \in L^{r'}(Q')\) with
If \(q_k < 1 + d/2\), then \(c u \in L^{r''}(Q')\) with
Note that \(r'' > r'\). If \(q_k \ge 1 + d/2\), then \(u \in L^\infty (Q')\) and thus \(cu \in L^p(Q')\). We set now \(q_{k+1}= \min (r',p)\). We observe that in both cases, \(cu \in L^{q_{k+1}}(Q')\). One can verify that the other terms of \(h''[u]\) also lie in \(L^{q_{k+1}}(Q')\). Therefore, by Theorem 3, \(v\in W^{2,1,q_{k+1}}(Q')\). If \(q_{k+1} \ge d+2\), we stop the construction of the sequence and set \(K=k+1\). It remains to prove that the construction of the sequence stops after finitely many iterations. If that was not the case, we would have that \(q_{k+1}= r'\), with \(r'\) defined in (60), for all \(k \in \mathbb {N}\), implying that
which is a contradiction. Now we know that \(v \in W^{2,1,q_K}(Q')\), with \(q_K \ge d+2\). This implies that \(u \in L^\infty (Q')\) and \(\nabla u \in L^\infty (Q',\mathbb {R}^d)\) (by Lemma 11) and thus that \(h''[u] \in L^p(Q')\). Finally, \(v \in W^{2,1,p}(Q')\) (by Theorem 3) and \(u \in W^{2,1,p}(Q)\), since u and v coincide on Q.
Observing that \(q_0\),...,\(q_K\) only depend on p and d, the reader can check that v (and thus u) can be bounded in \(W^{2,1,p}(Q')\) by a constant depending on R only. \(\square \)
Theorem 5
For \(q \in (1,\infty )\), the trace at time \(t=0\) of elements of \(W^{2,1,q}(Q')\) belongs to \(W^{2-2/q,q}(\varOmega )\).
Proof
See [19, Lemma 3.4, page 82]. \(\square \)
Theorem 6
Let \(p > d+2\). There exists \(C>0\) such that for all \(u_0 \in W^{2-2/p,p}(\mathbb {T}^d)\) and for all \(h \in L^p(Q)\), the unique solution u to (51) (with \(b= 0\) and \(c=0\)) satisfies the following estimate:
Proof
Consider the map \(u \in W^{2,1,p}(Q) \mapsto (u(\cdot ,0), \partial _t u - \sigma \varDelta u - h) \in W^{2-2/p,p}(\varOmega ),L^p(Q)).\) By Theorem 5, it is continuous and by Theorem 6, it is bijective. As a consequence of the open mapping theorem, its inverse is also continuous. The result follows. \(\square \)
Lemma 12
Let \(p>d+2\). There exists \(\delta \in (0,1)\) and \(C>0\) such that for all \(u \in W^{2,1,p}(Q)\),
Proof
See [19, Lemma II.3.3, page 80 and Corollary, page 342]. \(\square \)
Theorem 7
Let \(p>d+2\). For all \(\alpha \in (0,1)\), for all \(R>0\), there exist \(\beta \in (0,1)\) and \(C>0\) such that for all \(u_0 \in \mathcal {C}^{2+ \alpha }(\mathbb {T}^d)\), \(b \in \mathcal {C}^{\alpha ,\alpha /2}(Q,\mathbb {R}^d)\), \(c \in \mathcal {C}^{\alpha ,\alpha /2}(Q)\) and \(h \in \mathcal {C}^{\alpha ,\alpha /2}(Q)\) satisfying
the solution to (51) lies in \(\mathcal {C}^{2+\beta ,1+\beta /2}(Q)\) and satisfies \(\Vert u \Vert _{\mathcal {C}^{2+\beta ,1+\beta /2}(Q)} \le C\).
Proof
In the proof, C denotes constants that depend only on \(\alpha \) and R. Combining Theorem 4 and Lemma 12, we obtain that h[u] is Hölder continuous, with exponent \(\beta :=\min (\delta ,\alpha )\) (where \(\delta \) is given by Lemma 12; we use the fact that a product of Hölder functions is Hölder, with exponent equal to the minimum exponent), and \(\Vert h[u]\Vert _{\mathcal {C}^{\beta ,\beta /2}(Q)} \le C.\) By [19, Theorem IV.5.1, page 320], \(\Vert v \Vert _{\mathcal {C}^{2+\beta ,1+\beta /2}(Q)} \le C\). Since u and v coincide on \(\mathbb {T}^d\), the conclusion follows. \(\square \)
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Bonnans, J.F., Hadikhanloo, S. & Pfeiffer, L. Schauder Estimates for a Class of Potential Mean Field Games of Controls. Appl Math Optim 83, 1431–1464 (2021). https://doi.org/10.1007/s00245-019-09592-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00245-019-09592-z
Keywords
- Mean field games of controls
- Extended mean field games
- Strongly coupled mean field games
- Potential formulation
- Hölder estimates