Improved fast compressive tracking for low-altitude flying target tracking

Cheng, Yuanhao; Wang, Sunan; Yu, Daren

doi:10.1007/s11042-020-10343-4

Cited by 4 publications

(1 citation statement)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These agents have an autonomous ability to coordinate with each other. In multi-agent systems, the research on the system's collaboration control has mainly involved tracking [1][2][3][4], formation [5][6][7], swarm [8][9][10], rendezvous [11], distributed filtering [12], and consistency [13,14]. Collaboration consistency elucidates that the state of all agents tends toward the same tendency, and it illustrates the rule of interacting and transmitting information when agents cooperate with other agents; additionally, it describes the process of information exchange between each agent and other agents.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Model of Collaboration in Multi-Agent System Based on Evolutionary Game Theory

Gou

Deng

2021

Games

View full text Add to dashboard Cite

Multi-agent collaboration is greatly important in order to reduce the frequency of errors in message communication and enhance the consistency of exchanging information. This study explores the process of evolutionary decision and stable strategies among multi-agent systems, including followers, leaders, and loners, involved in collaboration based on evolutionary game theory (EGT). The main elements that affected the strategies are discussed, and a 3D evolution model is established. The evolutionary stability strategy (ESS) and stable conditions were analyzed subsequently. Numerical simulation results were obtained through MATLAB simulation, and they manifested that leaders play an important role in exchanging information with other agents, accepting agents’ state information, and sending messages to agents. Then, with the positivity of receiving and feeding back messages for followers, implementing message communication is profitable for the system, and the high positivity can accelerate the exchange of information. At the behavior level, reducing costs can strengthen the punishment of impeding the exchange of information and improve the positivity of collaboration to facilitate the evolutionary convergence toward the ideal state. Finally, the EGT results revealed that the possibility of collaboration between loners and others is improved, and the rewards are increased, thereby promoting the implementation of message communication that encourages leaders to send all messages, improve the feedback positivity of followers, and reduce the hindering degree of loners.

show abstract