DocumentCode
2713298
Title
An alpha derivative formulation of the Hamilton-Jacobi-Bellman equation Of Dynamic Programming
Author
Seiffertt, John
Author_Institution
Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
fYear
2009
fDate
14-19 June 2009
Firstpage
2854
Lastpage
2859
Abstract
The time scales calculus, which includes the study of the alpha derivative, is an emerging key area in mathematics. We extend this calculus to approximate dynamic programming. In particular, we investigate application of the alpha derivative, one of the fundamental dynamic derivatives of time scales. We present a alpha-derivative based derivation and proof of the Hamilton-Jacobi-Bellman equation, the solution of which is the fundamental problem in the field of dynamic programming. By drawing together the calculus of time scales and the applied area of stochastic control via approximate dynamic programming, we connect two major fields of research.
Keywords
approximation theory; calculus; dynamic programming; stochastic systems; Hamilton-Jacobi-Bellman equation; alpha derivative formulation; approximate dynamic programming; mathematics; stochastic control; time scales calculus; Approximation methods; Calculus; Costs; Differential equations; Dynamic programming; Intelligent robots; Mathematics; Partial differential equations; Programmable control; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location
Atlanta, GA
ISSN
1098-7576
Print_ISBN
978-1-4244-3548-7
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2009.5178990
Filename
5178990
Link To Document