## Principles of Dynamic Programming: Advanced theory and applications |

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### Contents

CHAPTER | 3 |

CHAPTER 2 | 55 |

Stochastic and Adaptive Systems | 119 |

Copyright | |

5 other sections not shown

### Common terms and phrases

20 Total profit Aircraft airplane airport algorithm allocation Appl applied assume Bellman block calculate calculus of variations capacity computational Consider the problem constraints control problem control processes control variables corresponding cost function curve defined denote density function Derive DEST PROFIT HRS determine discrete distribution dynamic programming estimate Euler equation example expected value Figure flight forward dynamic programming fuel functional equation given high-speed memory requirement HOUR ORG DEST increment initial condition interval iterative Lagrange multiplier linear Math Mathematical matrix maximize maximum method minimum cost function n-dimensional Nonlinear obtained operation optimal control optimal point optimal policy optimal trajectory optimization problem partial differential equation performance criterion plant principle of optimality probability density function problem of minimizing procedure quadratic quantity quantized random variables recurrence relation reservoir result Riccati equation S0TE scalar schedule sequence solution solve stage system equations Theory thermal tion vector x(k+l zero