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最优性方程
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  optimality equation
     By applying the transformation of the SMP to the discrete-time Markov chain(DTMC),the potential of the DTMC is used to obtain the sensitivity formula and optimality equation of SMP.
     将SMP转化为与之等价的离散时间Markov链 (DTMC) ,利用DTMC的性能势 ,对SMP进行灵敏度分析和性能优化 ,得到了SMP基于DTMC性能势的灵敏度分析公式和最优性方程 .
短句来源
     The average-Poisson equation is defined for infinite horizon average model and the optimality equation is induced in a compact action set.
     定义了平均Poisson方程,导出了平均代价模型在紧致行动集上的最优性方程
短句来源
     Based on performance potential theorem and Bellman optimality equation, it is easy to establish optimality equation, which we call performance potential-based Bellman optimality equation, for both average-cost and discounted-cost performance criteria.
     基于性能势理论及Bellman最优方程,很容易建立平均代价和折扣代价性能准则下的最优性方程,称之为基于性能势的Bellman最优方程。
短句来源
     This equation is used to define the α-potential,based on which the optimality equation satisfied by the optimal stationary policy is derived.
     基于α-势,导出了由最优平稳策略所满足的最优性方程.
短句来源
     Based on the α-potential, the optimality equation satisfied by the optimal stationary policy is given.
     基于α 势,给出了由最优平稳策略所满足的最优性方程.
短句来源
更多       
  optimality equations
     Optimality equations based performance potentials for a class of controlled closed queueing networks
     一类受控闭排队网络基于性能势的最优性方程
短句来源
     Moreover,the relationship of sensitivity formulas ,as well as that of the optimality equations,under the discounted cost criteria and the average cost criteria and the average cost criteria is established by using the vanishing discounted factor.
     此外,建立了在折扣准则与无穷时间平均代价准则(简称平均准则)下灵敏度公式及最优性方程之间的联系.
短句来源
     Based on a potential approach,the optimality equations satisfied by the optimal stationary policies are derived.
     基于性能势方法,导出了由最优平稳策略所满足的最优性方程.
短句来源
  “最优性方程”译为未确定词的双语例句
     Based on optimal Poisson equation and the optimal theorem with potentials, a lot of algorithms, such as policy iteration and value iteration, can be obtained.
     根据基于性能势的Bellman最优性方程以及最优性定理,可以发展求解MDP最优策略的策略迭代、数值迭代等算法。
短句来源
     By some results about Q-factor and potentials, the uniform Bellman optimizality equation and the learning formula for Q-factor are provided.
     利用Q函数与性能势的相关成果,获得了两种准则下Q函数的统一Bellman最优性方程以及统一的学习公式。
短句来源
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  optimality equation
In this stochastic stopping model, we prove that there exists an optimal deterministic and stationary policy and the optimality equation has a unique solution.
      
It is shown that both value functions satisfy the optimality equation and upper and lower bounds as well as conditions for equality for these functions are presented.
      
Under a Lyapunov function condition, we show that stationary policies obtained from the average reward optimality equation are not only average reward optimal, but indeed sample path average reward optimal, for almost all sample paths.
      
For the case of the switching arms, only of one which creates rewards, we solve explicitly the average optimality equation and prove that a myopic policy is average optimal.
      
We establish also a lexicographical policy improvement algorithm leading to Blackwell optimal policies and the relation between such policies and the Blackwell optimality equation.
      
更多          
  optimality equations
An analogy between the optimality equations and the governing equations for a set of certain static beams permits obtaining numerical solutions to the optimal control problem with the help of standard 'structural' FEM software.
      
From the optimality equations which are provided in this paper, we translate the average variance criterion into a new average expected cost criterion.
      
Controlled Markov chains with risk-sensitive criteria: Average cost, optimality equations, and optimal solutions
      
The approach uses an analogy between the optimality equations for control in the time domain and the governing equations for a set of static beams in the spatial domain.
      
Moreover,necessary andsufficient conditions are given so that the optimality equations have a bounded solution with an additional property.
      
更多          
  (optimality) equation
In this stochastic stopping model, we prove that there exists an optimal deterministic and stationary policy and the optimality equation has a unique solution.
      
It is shown that both value functions satisfy the optimality equation and upper and lower bounds as well as conditions for equality for these functions are presented.
      
Under a Lyapunov function condition, we show that stationary policies obtained from the average reward optimality equation are not only average reward optimal, but indeed sample path average reward optimal, for almost all sample paths.
      
For the case of the switching arms, only of one which creates rewards, we solve explicitly the average optimality equation and prove that a myopic policy is average optimal.
      
We establish also a lexicographical policy improvement algorithm leading to Blackwell optimal policies and the relation between such policies and the Blackwell optimality equation.
      
更多          


This paper deals with the performance optimization problem of a class of controlled closed queueing network systems (CQNS). We introduce two fundamental concepts: the discounted cost α-performance potentials and average cost performance potentials, and consider a fundamental relation between the two potentials. Under a general assumption, we establish directly the optimality equation for infinite time horizon average cost model and prove the existence of optimal solution in a compact action set by using properties...

This paper deals with the performance optimization problem of a class of controlled closed queueing network systems (CQNS). We introduce two fundamental concepts: the discounted cost α-performance potentials and average cost performance potentials, and consider a fundamental relation between the two potentials. Under a general assumption, we establish directly the optimality equation for infinite time horizon average cost model and prove the existence of optimal solution in a compact action set by using properties of the performance potentials, suggest an policy_optimality algorithm and give a numerical example to illustrate the application of the proposed algorithm.

研究一类受控闭排队网络系统的性能优化问题 .文章引进了两个基本概念 :折扣代价α 性能势和平均代价性能势 ,并且讨论了这两个性能势之间的一个关系式 .在一般的假设条件下 ,我们应用性能势的基本性质直接建立了无限时间水平平均代价模型的最优性方程 ,并且证明了在紧致集上最优解的存在性 .最后给出了一个策略优化的迭代算法并通过一个实际算例以说明该算法的效果 .

This paper deals with the average cost optimization problem for a class of discrete time Markov control processes. Under quite general assumptions, the optimality equation is directly established and the existence theorem of optimal solution is proved for infinite time average cost model in a compact action set by using basic properties of the Markov performance potentials. The iterate algorithm for solving optimal stationary control strategy is suggested and the convergence problem of this algorithm is discussed....

This paper deals with the average cost optimization problem for a class of discrete time Markov control processes. Under quite general assumptions, the optimality equation is directly established and the existence theorem of optimal solution is proved for infinite time average cost model in a compact action set by using basic properties of the Markov performance potentials. The iterate algorithm for solving optimal stationary control strategy is suggested and the convergence problem of this algorithm is discussed. Finally, a numerical example is analyzed to illustrate the application of the proposed algorithm.

研究了一类离散时间 Markov控制过程平均代价性能最优控制决策问题 .应用Markov性能势的基本性质 ,在很一般性的假设条件下 ,直接导出了无限时间平均代价模型在紧致行动集上的最优性方程及其解的存在性定理 .提出了求解最优平稳控制策略的迭代算法 ,并讨论了这种算法的收敛性问题 .最后通过分析一个实例来说明这种算法的应用 .

Optimization algorithms are studied for a class of continuous-time Markov control processes (CTMCPs) with infinite horizon average-cost criteria and compact action set. By using the formula of performance potentials and an average-cost optimality equation for CTMCPs, a policy iteration algorithm and a value iteration algorithm are derived, which can lead to an optimal or suboptimal stationary policy in a finite number of iterations. The convergence of these algorithms is established, without the assumption...

Optimization algorithms are studied for a class of continuous-time Markov control processes (CTMCPs) with infinite horizon average-cost criteria and compact action set. By using the formula of performance potentials and an average-cost optimality equation for CTMCPs, a policy iteration algorithm and a value iteration algorithm are derived, which can lead to an optimal or suboptimal stationary policy in a finite number of iterations. The convergence of these algorithms is established, without the assumption of the corresponding iteration operator being an sp-contraction. A numerical example of queuing networks shows advantages of the proposed value iteration method.

研究一类连续时间 Markov控制过程 ( CTMCP)在紧致行动集上关于平均代价性能准则的优化算法。根据 CTMCP的性能势公式和平均代价最优性方程 ,导出了求解最优或次最优平稳控制策略的策略迭代算法和数值迭代算法 ,在无需假设迭代算子是 sp-压缩的条件下 ,给出了这两种算法的收敛性证明。最后通过分析一个受控排队网络的例子说明了这种方法的优越性

 
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