Determination of the levels s and S by dynamic programming

1972 ◽  
pp. 190-202
Author(s):  
R. N. van Hees ◽  
W. Monhemius
Keyword(s):  
Dynamic Programming

Dynamic programming, pattern recognition and location of faults in complex systems

1966 ◽  
Vol 3 (01) ◽  
pp. 268-271
Author(s):  
Richard Bellman
Keyword(s):  
Complex System ◽  
Functional Equation ◽  
Pattern Recognition ◽  
Dynamic Programming ◽  
Decomposition Technique ◽  
Extended State ◽  
Identification Problems ◽  
State Variable ◽  
Computational Solution

In a previous paper devoted to an application of dynamic programming to pattern recognition [1], we pointed out that some identification problems could be regarded as generalized trajectory processes. The functional equation technique [2] could then be employed to obtain an analytic formulation of the determination of optimal search techniques. In many cases, however, (for example, in chess or checkers), a straightforward use of the functional equation is impossible because of dimensionality difficulties. In circumventing these obstacles to effective computational solution, we employed a decomposition technique which we called “stratification” [1, 3]. In this paper, we present a different way of avoiding the dimensionality problem, based upon the concept of “extended state variable”. To indicate the utility of the concept, we shall apply it to the problem of finding a fault in a complex system.

Determination of the best main serial chain in nonserial dynamic programming networks

1993 ◽  
Vol 67 (2) ◽  
pp. 248-258
Author(s):  
Chae Y. Lee ◽  
Augustine O. Esogbue
Keyword(s):  
Dynamic Programming ◽  
Serial Chain

Play Calling Strategy in American Football: A Game-Theoretic Stochastic Dynamic Programming Approach

1999 ◽  
Vol 13 (2) ◽  
pp. 103-113 ◽  
Author(s):  
Jess S. Boronico ◽  
Scott L. Newbert
Keyword(s):  
Dynamic Programming ◽  
Stochastic Dynamic Programming ◽  
Quantitative Methods ◽  
American Football ◽  
Programming Approach ◽  
Stochastic Dynamic ◽  
Theoretic Approach ◽  
Dynamic Programming Approach ◽  
Game Theoretic

This manuscript presents a model to assist in the determination of optimal American football play selection for first down and goal situations. A game theoretic approach is embedded within a stochastic dynamic programming formulation, resulting in a mixed strategy satisfying the ex-ante declared objective of maximizing the probability of scoring a touchdown. The methodology provides a quantitative framework to a problem that impacts on team performance and addresses a gap in the literature concerning the application of quantitative methods to sports.

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