Abstract

This paper designs an incentive strategy for a class of stochastic Stackelberg games in finite horizon and infinite horizon, respectively. The obtained incentive Stackelberg strategy works well in the sense that the leader will get his desired solution in the end. Different from the existing works, the state-dependent noise is considered in the design of the incentive Stackelberg strategy. Moreover, the mean-square stabilization can be guaranteed by the follower. The algorithm procedure is put forward to obtain effectively the incentive feedback Stackelberg strategy in infinite horizon. Finally, two examples are given to shed light on the effectiveness of the proposed algorithm procedure.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.