Decentralized stochastic adaptive nash games
Decentralized stochastic adaptive nash games
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DOI：
10.1002/oca.4660040206
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发表时间：
1983-04
影响因子：
1.8
通讯作者：
Y. M. Chan;J. Cruz
中科院分区：
文献类型：
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作者：
Y. M. Chan;J. Cruz
研究了具有未知参数和多个具有各自目标的决策者或控制器的随机系统的优化问题。针对“一步延迟共享模式”下的分散随机自适应纳什对策，提出了两种显式自校正型算法。第一个算法是一个特设的政策形式的约束，而第二个是基于静态纳什博弈理论的扩展。对一个简化的经济系统的仿真结果表明，这些算法能够稳定系统沿着目标路径。
The optimization of stochastic systems with unknown parameters and multiple decision-makers or controllers each having his own objective is considered. Two explicit self-tuning type algorithms are proposed for decentralized stochastic adaptive Nash games under the ‘one-step-delay sharing pattern’. The first algorithm is an ad hoc constraint on the policy form, whereas the second one is based on an extension from static Nash game theory. Simulation results on a simplified economic system indicate that these algorithms are capable of stabilizing a system along targeted paths.