Asynchronous control for coupled Markov decision systems
Asynchronous control for coupled Markov decision systems
复制标题
耦合马尔可夫决策系统的异步控制
DOI：
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发表时间：
2012
期刊：
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通讯作者：
M. Neely
中科院分区：
文献类型：
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作者：
M. Neely
本文考虑了一组独立的马尔可夫决策系统的最优控制，这些系统在各自的状态空间上异步运行。每个系统的决策影响：（i）当前状态所花费的时间，（ii）所产生的惩罚向量，以及（iii）下一个状态转移概率。一个示例是执行单独任务但共享公共无线信道的智能设备的网络。该模型还可以应用于数据中心调度和各种类型的信息物理网络。组合状态空间随着系统的数量呈指数增长。然而，开发了一个简单的策略，其中每个系统做出单独的决策。总的复杂性只会随着系统数量的增加而线性增长，并且由此产生的性能可以任意地接近最佳。
This paper considers optimal control for a collection of separate Markov decision systems that operate asynchronously over their own state spaces. Decisions at each system affect: (i) the time spent in the current state, (ii) a vector of penalties incurred, and (iii) the next-state transition probabilities. An example is a network of smart devices that perform separate tasks but share a common wireless channel. The model can also be applied to data center scheduling and to various types of cyber-physical networks. The combined state space grows exponentially with the number of systems. However, a simple strategy is developed where each system makes separate decisions. Total complexity grows only linearly in the number of systems, and the resulting performance can be pushed arbitrarily close to optimal.