Calculus of variations and optimal control; optimization Dynamic programming and Hamilton-Jacobi theory Concept
Hamilton–Jacobi–Bellman equation
Summary
The Hamilton–Jacobi–Bellman equation is a first-order partial differential equation for the value function of an optimal control problem. It is the continuous-time form of the principle of dynamic programming: an optimal strategy stays optimal from every later state. A solution gives the optimal cost from every starting point and, through a pointwise minimization, an optimal feedback control. In general the value function is not differentiable, and the equation is understood in the sense of viscosity solutions.
Where this leads
7 pages build on this one.
Further reading
About this page
| Tag | SJP9HW82VX |
|---|---|
| URI | m2://SJP9HW82VX |
| Kind | concept |
| Writing | W0 stub |
| MSC | 49L12, 49L20 |
| Same as |
Markdown · JSON · Edit on GitHub
What this page needs for W1
- an inventory row: the row of the inventory that the node accounts for (0 of 1)
- a source with a locator (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.
What links here
Used by
- Stochastic optimal control
- Merton's portfolio problem
- Dynamic programming in continuous time
- Viscosity solution of the Hamilton–Jacobi–Bellman equation
- Hamilton–Jacobi–Isaacs equation
- Mean-field game
- Verification theorem