Owing to the ubiquitous use of smartphones by soldiers, military researchers have an increasing interest in potentially problematicside effects such as smartphone overdependence. This raises a question regarding the p...Owing to the ubiquitous use of smartphones by soldiers, military researchers have an increasing interest in potentially problematicside effects such as smartphone overdependence. This raises a question regarding the psychological mechanisms underlying thepotentially self-damaging use of smartphones. Here, we address this question by analyzing how heterogeneity in commander’sgood leadership explains subordinate soldiers’ differences in self-control and smartphone use. Specifically, we found thatsubordinate soldiers who thought their commander's leadership was good were self-regulated, less dependent on smartphones,less stressed, and finally had good mental health. This result indicates that commander’s good leadership can be used toestimate whether subordinate soldiers exert control over their impulses and use their smartphones properly. Thus, the currentfindings help to identify external factors that lead to a better understanding of problematic smartphone use and can potentiallyhelp to design appropriate preventive mechanisms or interventions that target commander’s good leadership.展开更多
War rehearsals have become increasingly important in national security due to the growing complexity of international affairs.However,traditional rehearsal methods,such as military chess simulations,are inefficient an...War rehearsals have become increasingly important in national security due to the growing complexity of international affairs.However,traditional rehearsal methods,such as military chess simulations,are inefficient and inflexible,with particularly pronounced limitations in command and decision-making.The overwhelming volume of information and high decision complexity hinder the realization of autonomous and agile command and control.To address this challenge,an intelligent warfare simulation framework named Command-Agent is proposed,which deeply integrates large language models(LLMs)with digital twin battlefields.By constructing a highly realistic battlefield environment through real-time simulation and multi-source data fusion,the natural language interaction capabilities of LLMs are leveraged to lower the command threshold and to enable autonomous command through the Observe-Orient-Decide-Act(OODA)feedback loop.Within the Command-Agent framework,a multimodel collaborative architecture is further adopted to decouple the decision-generation and command-execution functions of LLMs.By combining specialized models such as Deep Seek-R1 and MCTool,the limitations of single-model capabilities are overcome.MCTool is a lightweight execution model fine-tuned for military Function Calling tasks.The framework also introduces a Vector Knowledge Base to mitigate hallucinations commonly exhibited by LLMs.Experimental results demonstrate that Command-Agent not only enables natural language-driven simulation and control but also deeply understands commander intent.Leveraging the multi-model collaborative architecture,during red-blue UAV confrontations involving 2 to 8 UAVs,the integrated score is improved by an average of 41.8%compared to the single-agent system(MCTool),accompanied by a 161.8%optimization in the battle loss ratio.Furthermore,when compared with multi-agent systems lacking the knowledge base,the inclusion of the Vector Knowledge Base further improves overall performance by 16.8%.In comparison with the general model(Qwen2.5-7B),the fine-tuned MCTool leads by 5%in execution efficiency.Therefore,the proposed Command-Agent introduces a novel perspective to the military command system and offers a feasible solution for intelligent battlefield decision-making.展开更多
In this paper a model of military command process under the combat situation is presented. The model is based on the Lanchester Equations and Fuzzy Decision Theory. The decision of a military commander is usually a pr...In this paper a model of military command process under the combat situation is presented. The model is based on the Lanchester Equations and Fuzzy Decision Theory. The decision of a military commander is usually a process from precise to fuzzy and then from fuzzy to precise,and the model fitted this process well. The model was used in a Warfare Simulation System whose object is to evaluate the effectiveness of the military C3I systems.展开更多
Cicero tried to take advantage of the War of Mutina in spring 44 BC,to vilify Mark Antony who,in his view,was the mortal foe to the res publica libera.In order to achieve his aim,Cicero used his letter-exchange with t...Cicero tried to take advantage of the War of Mutina in spring 44 BC,to vilify Mark Antony who,in his view,was the mortal foe to the res publica libera.In order to achieve his aim,Cicero used his letter-exchange with the military commanders in North and West Italy as well as in Africa to exert his infl uence and assure their alliance against Antony.Cicero employed various tactics in his letters to persuade and integrate those commanders into his framework.Those tactics functioned for some time during the war but failed eventually.Due to the formidable alliance of the Caesarian party and the still scattered powers of the Republicans,Cicero’s maneuver to remove Antony only by means of political advocacy failed.展开更多
The dynamic weapon-target assignment(DWTA)problem is an important issue in the field of military command and control.An asset-based DWTA optimization model was proposed with four kinds of constraints considered,includ...The dynamic weapon-target assignment(DWTA)problem is an important issue in the field of military command and control.An asset-based DWTA optimization model was proposed with four kinds of constraints considered,including capability constraints,strategy constraints,resource constraints and engagement feasibility constraints.A general"virtual"representation of decisions was presented to facilitate the generation of feasible decisions.The representation is in essence the permutation of all assignment pairs.A construction procedure converts the permutations into real feasible decisions.In order to solve this problem,three evolutionary decision-making algorithms,including a genetic algorithm and two memetic algorithms,were developed.Experimental results show that the memetic algorithm based on greedy local search can generate obviously better DWTA decisions,especially for large-scale problems,than the genetic algorithm and the memetic algorithm based on steepest local search.展开更多
基金supported by 2023 Research Fund of Korea Military Academy(Hwarangdae Research Institute,RN:2023B1012).
文摘Owing to the ubiquitous use of smartphones by soldiers, military researchers have an increasing interest in potentially problematicside effects such as smartphone overdependence. This raises a question regarding the psychological mechanisms underlying thepotentially self-damaging use of smartphones. Here, we address this question by analyzing how heterogeneity in commander’sgood leadership explains subordinate soldiers’ differences in self-control and smartphone use. Specifically, we found thatsubordinate soldiers who thought their commander's leadership was good were self-regulated, less dependent on smartphones,less stressed, and finally had good mental health. This result indicates that commander’s good leadership can be used toestimate whether subordinate soldiers exert control over their impulses and use their smartphones properly. Thus, the currentfindings help to identify external factors that lead to a better understanding of problematic smartphone use and can potentiallyhelp to design appropriate preventive mechanisms or interventions that target commander’s good leadership.
文摘War rehearsals have become increasingly important in national security due to the growing complexity of international affairs.However,traditional rehearsal methods,such as military chess simulations,are inefficient and inflexible,with particularly pronounced limitations in command and decision-making.The overwhelming volume of information and high decision complexity hinder the realization of autonomous and agile command and control.To address this challenge,an intelligent warfare simulation framework named Command-Agent is proposed,which deeply integrates large language models(LLMs)with digital twin battlefields.By constructing a highly realistic battlefield environment through real-time simulation and multi-source data fusion,the natural language interaction capabilities of LLMs are leveraged to lower the command threshold and to enable autonomous command through the Observe-Orient-Decide-Act(OODA)feedback loop.Within the Command-Agent framework,a multimodel collaborative architecture is further adopted to decouple the decision-generation and command-execution functions of LLMs.By combining specialized models such as Deep Seek-R1 and MCTool,the limitations of single-model capabilities are overcome.MCTool is a lightweight execution model fine-tuned for military Function Calling tasks.The framework also introduces a Vector Knowledge Base to mitigate hallucinations commonly exhibited by LLMs.Experimental results demonstrate that Command-Agent not only enables natural language-driven simulation and control but also deeply understands commander intent.Leveraging the multi-model collaborative architecture,during red-blue UAV confrontations involving 2 to 8 UAVs,the integrated score is improved by an average of 41.8%compared to the single-agent system(MCTool),accompanied by a 161.8%optimization in the battle loss ratio.Furthermore,when compared with multi-agent systems lacking the knowledge base,the inclusion of the Vector Knowledge Base further improves overall performance by 16.8%.In comparison with the general model(Qwen2.5-7B),the fine-tuned MCTool leads by 5%in execution efficiency.Therefore,the proposed Command-Agent introduces a novel perspective to the military command system and offers a feasible solution for intelligent battlefield decision-making.
文摘In this paper a model of military command process under the combat situation is presented. The model is based on the Lanchester Equations and Fuzzy Decision Theory. The decision of a military commander is usually a process from precise to fuzzy and then from fuzzy to precise,and the model fitted this process well. The model was used in a Warfare Simulation System whose object is to evaluate the effectiveness of the military C3I systems.
文摘Cicero tried to take advantage of the War of Mutina in spring 44 BC,to vilify Mark Antony who,in his view,was the mortal foe to the res publica libera.In order to achieve his aim,Cicero used his letter-exchange with the military commanders in North and West Italy as well as in Africa to exert his infl uence and assure their alliance against Antony.Cicero employed various tactics in his letters to persuade and integrate those commanders into his framework.Those tactics functioned for some time during the war but failed eventually.Due to the formidable alliance of the Caesarian party and the still scattered powers of the Republicans,Cicero’s maneuver to remove Antony only by means of political advocacy failed.
基金Supported by the National Natural Science Foundation of China(Grant No.60374069)the Foundation of the Key Laboratory of Complex Systems and Intelligent Science,Institute of Automation,Chinese Academy of Sciences(Grant No.20060104)
文摘The dynamic weapon-target assignment(DWTA)problem is an important issue in the field of military command and control.An asset-based DWTA optimization model was proposed with four kinds of constraints considered,including capability constraints,strategy constraints,resource constraints and engagement feasibility constraints.A general"virtual"representation of decisions was presented to facilitate the generation of feasible decisions.The representation is in essence the permutation of all assignment pairs.A construction procedure converts the permutations into real feasible decisions.In order to solve this problem,three evolutionary decision-making algorithms,including a genetic algorithm and two memetic algorithms,were developed.Experimental results show that the memetic algorithm based on greedy local search can generate obviously better DWTA decisions,especially for large-scale problems,than the genetic algorithm and the memetic algorithm based on steepest local search.
