Hamilton-Jacobi Equations and Two-Person Zero-Sum Differential Games with Unbounded Controls
Hong Qiu, Jiongmin Yong

TL;DR
This paper studies two-player zero-sum differential games with unbounded controls, characterizing value functions as viscosity solutions to Hamilton-Jacobi equations and proving uniqueness without convexity assumptions.
Contribution
It establishes the existence and uniqueness of viscosity solutions for Hamilton-Jacobi equations with superlinear growth Hamiltonians in the context of unbounded controls.
Findings
Value functions are characterized as unique viscosity solutions.
Existence of the game value when Isaacs' condition holds.
Sharp coercivity conditions ensure finiteness of value functions.
Abstract
A two-person zero-sum differential game with unbounded controls is considered. Under proper coercivity conditions, the upper and lower value functions are characterized as the unique viscosity solutions to the corresponding upper and lower Hamilton--Jacobi--Isaacs equations, respectively. Consequently, when the Isaacs' condition is satisfied, the upper and lower value functions coincide, leading to the existence of the value function. Due to the unboundedness of the controls, the corresponding upper and lower Hamiltonians grow super linearly in the gradient of the upper and lower value functions, respectively. A uniqueness theorem of viscosity solution to Hamilton--Jacobi equations involving such kind of Hamiltonian is proved, without relying on the convexity/concavity of the Hamiltonian. Also, it is shown that the assumed coercivity conditions guaranteeing the finiteness of the upper…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOptimization and Variational Analysis · Nonlinear Partial Differential Equations · Mathematical Biology Tumor Growth
