Research progress in decision-making for unmanned intelligent swarm system and control
In the pursuit of furthering the understanding of unmanned swarm systems,this paper embarks on an expansive journey,delving even deeper into the intricacies of cooperative decision-making and game control.The two methodological pillars,carefully chosen for their unique contributions,play a pivotal role in steering unmanned swarm systems toward heightened efficiency and adaptability across diverse environments.First,the implementation of cooperative control stands as a cornerstone,fostering enhanced communication and collaboration among agents within the unmanned swarm system.This strategic approach not only minimizes conflicts but also streamlines tasks,contributing substantially to the augmenta-tion of system efficiency.Cooperative control establishes a foundation for improved information exchange and seamless cooperation by promoting a cohesive environment where agents work in tandem.Second,the integration of game control methodologies plays a pivotal role in empowering agents to navigate conflicts of interest effectively.This approach goes beyond conflict resolution;it actively contributes to elevating decision-making processes and optimizing the overall inter-ests of the cluster system.The dynamic nature of game control ensures that agents can strategically navigate complex sce-narios,maximizing collective interests and ensuring the sustained efficiency of the unmanned swarm system.Additionally,in practical large-scale problems,a balanced combination of cooperation and games enhances the adaptive capabilities of intelligent system clusters in diverse environments.This approach effectively resolves conflicts of interest and decision-making challenges that may arise between agents.Regarding the implementation of the two methods,this study concen-trates on utilizing the collaborative control method for tasks such as formation control,cluster path planning,and cluster task collaboration.Specific technical implementations are allocated to corresponding sub-items.The game control methods center around various game types,including self-play,evolutionary play,and reinforcement learning play.These approaches offer new prospects for addressing optimization challenges in cluster control.This study comprehensively reviews the application of cooperative and game control methods in the unmanned swarm system.Explicit explanations of fundamental concepts,including agents,swarm intelligence,and unmanned swarm systems,are provided to establish a basic understanding for readers.Subsequently,the mathematical models of cooperative and game control,swarm coopera-tion and game decisions,swarm cooperative control methods,swarm game control methods,and other algorithms are intro-duced.The emphasis is placed on the theoretical foundations of cooperative decision-making and game control,along with their applications in improving overall system performance in the unmanned swarm system.Furthermore,the paper delves into illustrative application scenarios,providing concrete examples of how swarm cooperation and game control methodolo-gies find practical relevance across diverse fields.These exemplary cases span a spectrum of industries,including intelli-gent transportation,unmanned aerial vehicle(UAV)formation,logistics and distribution,and military domains.The paper offers valuable insights into the versatility and adaptability of unmanned swarm systems by demonstrating the tangible applications of these technologies in real-world settings.Finally,the paper discusses future research directions and chal-lenges,emphasizing the necessity for new technologies and methods to address evolving needs and problems.The high-lighted complex challenges,including the intricacy of large-scale swarm systems,collaboration among heterogeneous agents,adaptability to dynamic environments,autonomy of clusters,interpretability and safety of unmanned swarm sys-tems,and self-healing capability,undoubtedly serve as key research focal points for future unmanned systems.Overall,this paper serves as a comprehensive guide and reference,not only delving into the theoretical foundations but also provid-ing practical insights into the application of cooperative decision-making and game control in unmanned swarm systems.The forward-looking approach of this paper positions it as a valuable resource for those seeking to advance the field,foster development and innovation,and contribute to the ongoing scientific and technological progress in this domain.
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