基本的解法有三种：动态规划法(dynamic programming methods)，蒙特卡罗方法(Monte Carlo methods)和时间差分法(temporal difference)。
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Traditional methods include Dynamic Programming, Greedy Algorithms, Local Search Heuristics and Branch and Bound algorithms.
传统的求解方法包括动态规划法、贪婪算法、局部搜索法和分支定界法等。
In this article, we introduce the principle of optimality in dynamic programming and some methods for solving certain simple variable and multi-variable problems.
本文引述了动态规划中的最优化原则和一些有关单变量和多变量问题的求解方法。
Dynamic programming is a methods in the solution of multistage decision making process.
动态规划法是解决多阶段决策过程最优化的一种方法。
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