Incentive feedback Stackelberg strategy for the discrete-time stochastic systems

Incentive feedback Stackelberg strategy for the discrete-time stochastic systems
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离散时间随机系统的激励反馈Stackelberg策略

DOI:
10.1016/j.jfranklin.2022.11.001
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发表时间:
2022-11
期刊:
Journal of the Franklin Institute
影响因子:
--
通讯作者:
Weihai Zhang
Weihai Zhang
中科院分区:
其他
文献类型:
--
作者:
Wenhui Gao;Yaning Lin;Weihai Zhang

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研究离散随机系统的激励Stackelberg策略的设计问题。现有的研究大多是关于确定性系统和连续时间随机系统的。虽然有许多方法可以帮助领导者达到团队最优价值,但由于条件期望的参与,离散随机系统的激励Stackelberg策略的设计更加困难和复杂。在本文中,这个问题研究了有限地平线的情况下,无限地平线的情况。此外,均方稳定性由跟随器保证。此外,对于无限时域情形,给出了具体的算法步骤,方便地得到了激励反馈Stackelberg策略。最后通过两个算例验证了算法的有效性.
The paper is devoted to designing an incentive Stackelberg strategy for the discrete-time stochastic systems. Most of the existing works are about the deterministic systems and the continuous-time stochastic systems. Although many methods have been used to help the leader to attain his team-optimal value, due to the involvement of the conditional expectation, the design of the incentive Stackelberg strategy for the discrete-time stochastic systems is more difficult and complicated. In this paper, this problem is studied for both the finite horizon case and the infinite horizon situation. Also, the mean-square stability is guaranteed by the follower. In addition, for the infinite horizon case, the specific algorithm procedure is put forward to obtain the incentive feedback Stackelberg strategy conveniently. At last, two examples are given to verify the effectiveness of the proposed algorithm procedure.
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